From 440d04895aa63f401bfdbadec86c46fe4570f661 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Istv=C3=A1n=20Zolt=C3=A1n=20Szab=C3=B3?= Date: Wed, 10 Sep 2025 11:13:10 +0200 Subject: [PATCH 01/12] [SEARCH] Emphasizes the datastore capabilities of ES on landing page. --- solutions/search.md | 22 ++++++++++++++++------ 1 file changed, 16 insertions(+), 6 deletions(-) diff --git a/solutions/search.md b/solutions/search.md index 54d1ee3db9..572b816264 100644 --- a/solutions/search.md +++ b/solutions/search.md @@ -14,20 +14,30 @@ products: # Elasticsearch -{{es}} enables you to build powerful search experiences for websites, applications, and enterprise data using Elastic's unified platform. +{{es}} as a toolbox for your search use case enables you to build powerful search experiences for websites, applications, and enterprise data using Elastic's unified platform. -## Use cases +## {{es}} powers search -Here are a few common real-world applications: +All of the search capabilities you find on this page are possible because {{es}} is not just a search engine, but it’s also a scalable, cost-efficient [data store](/manage-data/data-store.md). +You can bring in many types of data, index them in near real time, and keep them stored in a way that makes them both searchable and analyzable. Common examples include, but are not limited to: + +* **Textual data**: documents, logs, articles, or transcripts. +* **Numerical data**: metrics, performance data, sensor readings. +* **Geospatial data**: coordinates, maps, and location-based signals. +* **Vector data**: embeddings from {{ml}} models for semantic or hybrid search. + +By bringing all these capabilities together, Elasticsearch serves as a powerful data store, a geospatial search engine, a vector database, and more, all within a single technology. It forms the foundation of Elastic's unified data and search platform, enabling you to work with different data types seamlessly. To learn more, refer to the [{{es}} data store overview](/manage-data/data-store.md). + +## Search use cases + +Think of {{es}} as a set of powerful building blocks. You bring in your own data, text, logs, metrics, events, vectors, or geospatial information, and {{es}} gives you the tools to store, search, and analyze it. By combining these capabilities, you can design and build the search and discovery experiences that fit your needs, from product catalogs to knowledge bases, chatbots, or geospatial applications. | Use case | Business goals | Technical requirements | | ------------------------------------ | ------------------------------------------------------------------ | ------------------------------------------------------------- | -| **Vector search/hybrid search** | Run nearest neighbour search, combine with text for hybrid results | Dense embeddings, sparse embeddings, combined with text/BM25 | +| **Vector search/hybrid search** | Run nearest neighbour search, combine with text for hybrid results | Dense embeddings, sparse embeddings, combined with text/BM25 | | **Ecommerce/product catalog search** | Provide fast, relevant, and up-to-date results, faceted navigation | Inventory sync, user behavior tracking, results caching | | **Workplace/knowledge base search** | Search across range of data sources, enforcing permissions | Third-party connectors, document-level security, role mapping | | **Website search** | Deliver relevant, up-to-date results | Web crawling, incremental indexing, query caching | | **Customer support search** | Surface relevant solutions, manage access controls, track metrics | Knowledge graph, role-based access, analytics | | **Chatbots/RAG** | Enable natural conversations, provide context, maintain knowledge | Vector search, ML models, knowledge base integration | | **Geospatial search** | Process location queries, sort by proximity, filter by area | Geo-mapping, spatial indexing, distance calculations | - - From a9131c9862ad73f6a6f79c8eeecd084200f8fcad Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Istv=C3=A1n=20Zolt=C3=A1n=20Szab=C3=B3?= Date: Thu, 11 Sep 2025 13:36:46 +0200 Subject: [PATCH 02/12] More edits. --- solutions/search.md | 25 ++++++++++++++++++++----- 1 file changed, 20 insertions(+), 5 deletions(-) diff --git a/solutions/search.md b/solutions/search.md index 572b816264..693dc52c1d 100644 --- a/solutions/search.md +++ b/solutions/search.md @@ -12,11 +12,26 @@ products: - id: kibana --- -# Elasticsearch +# The Elasticsearch solution and search use case -{{es}} as a toolbox for your search use case enables you to build powerful search experiences for websites, applications, and enterprise data using Elastic's unified platform. +The {es} solution and serverless project type combines the core {es} data store, search engine, and vector database technologies with specialized user interfaces and tools, giving you the building blocks to create, deploy, and run your own search applications. -## {{es}} powers search +## The {es} solution + +The Elasticsearch solution and serverless project type provides specialized user interfaces and tools designed to simplify the implementation of search applications: + +* **Search and discovery interfaces**: Discover and Dashboards for exploring data, building visualizations, and creating search experiences. +* **Management interfaces**: Index Management and other tools for configuring and optimizing your search implementation. +* **Search relevance tools**: Purpose-built UIs for managing synonyms, query rules, and other relevance-enhancing features. +* **AI toolkit**: RAG Playground and inference endpoints management for building AI-enhanced search experiences. +* **Complete Elasticsearch REST API**: Full access to Elasticsearch's comprehensive APIs for indexing, searching, and managing data. +* **Deployment flexibility**: Run in Elastic Cloud, Elastic Serverless, or self-managed environments with consistent interfaces. + +## Use cases + +You can approach {{es}} use cases from two complementary angles: first, as a data store and vector database where you bring in and manage different types of data, and second, as a search solution where you use those core capabilities as building blocks to create tailored search applications. + +### Data store and vector database use case All of the search capabilities you find on this page are possible because {{es}} is not just a search engine, but it’s also a scalable, cost-efficient [data store](/manage-data/data-store.md). You can bring in many types of data, index them in near real time, and keep them stored in a way that makes them both searchable and analyzable. Common examples include, but are not limited to: @@ -26,9 +41,9 @@ You can bring in many types of data, index them in near real time, and keep them * **Geospatial data**: coordinates, maps, and location-based signals. * **Vector data**: embeddings from {{ml}} models for semantic or hybrid search. -By bringing all these capabilities together, Elasticsearch serves as a powerful data store, a geospatial search engine, a vector database, and more, all within a single technology. It forms the foundation of Elastic's unified data and search platform, enabling you to work with different data types seamlessly. To learn more, refer to the [{{es}} data store overview](/manage-data/data-store.md). +By bringing all these capabilities together, Elasticsearch serves as a powerful data store, a geospatial search engine, a vector database, and more, all within a single technology. It forms the foundation of Elastic's unified data and search platform, enabling you to work with different data types seamlessly. To learn more, refer to the [{{es}} data store overview](/manage-data/data-store.md). -## Search use cases +### Search use case Think of {{es}} as a set of powerful building blocks. You bring in your own data, text, logs, metrics, events, vectors, or geospatial information, and {{es}} gives you the tools to store, search, and analyze it. By combining these capabilities, you can design and build the search and discovery experiences that fit your needs, from product catalogs to knowledge bases, chatbots, or geospatial applications. From 80b4b6c387f7c6d96f5d9afd43f9ea6af9d42a6e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Istv=C3=A1n=20Zolt=C3=A1n=20Szab=C3=B3?= Date: Wed, 17 Sep 2025 15:19:01 +0200 Subject: [PATCH 03/12] Further edits. --- solutions/search.md | 58 ++++++++++++++++++++++++++++----------------- 1 file changed, 36 insertions(+), 22 deletions(-) diff --git a/solutions/search.md b/solutions/search.md index 693dc52c1d..d17c0564c8 100644 --- a/solutions/search.md +++ b/solutions/search.md @@ -12,40 +12,47 @@ products: - id: kibana --- -# The Elasticsearch solution and search use case +# The Elasticsearch solution -The {es} solution and serverless project type combines the core {es} data store, search engine, and vector database technologies with specialized user interfaces and tools, giving you the building blocks to create, deploy, and run your own search applications. +The {es} solution and serverless project type position {es} as a comprehensive platform: a scalable data store, a powerful search engine, and a vector database in one. At its core, {es} is a distributed datastore that can ingest, index, and manage various types of data in near real-time, making them both searchable and analyzable. With specialized user interfaces and tools, it provides the flexibility to create, deploy, and run a wide range of applications, from search to analytics to AI-driven solutions. -## The {es} solution +## What the {es} solution provides -The Elasticsearch solution and serverless project type provides specialized user interfaces and tools designed to simplify the implementation of search applications: +The {es} solution and serverless project type include specialized user interfaces and tools that simplify working with {es}: -* **Search and discovery interfaces**: Discover and Dashboards for exploring data, building visualizations, and creating search experiences. -* **Management interfaces**: Index Management and other tools for configuring and optimizing your search implementation. -* **Search relevance tools**: Purpose-built UIs for managing synonyms, query rules, and other relevance-enhancing features. -* **AI toolkit**: RAG Playground and inference endpoints management for building AI-enhanced search experiences. -* **Complete Elasticsearch REST API**: Full access to Elasticsearch's comprehensive APIs for indexing, searching, and managing data. -* **Deployment flexibility**: Run in Elastic Cloud, Elastic Serverless, or self-managed environments with consistent interfaces. +* **Ingestion tools**: Content connectors, crawlers, file upload function, and indexing APIs for ingesting and storing data +* **Data management and discovery**: Discover and Dashboards for exploring data, building visualizations, and creating interactive experiences +* **Management interfaces**: Index Management and other tools for configuring and optimizing your stored data and implementation +* **Search relevance tools**: Purpose-built UIs for managing synonyms, query rules, and other relevance-enhancing features +* **AI toolkit**: RAG Playground and inference endpoints management for building AI-enhanced applications +* **Complete {es} REST API**: Full access to {es}'s comprehensive APIs for indexing, searching, and managing data +* **Deployment flexibility**: Run in Elastic Cloud, Elastic Serverless, or self-managed environments with consistent interfaces -## Use cases +## Core capabilities and use cases -You can approach {{es}} use cases from two complementary angles: first, as a data store and vector database where you bring in and manage different types of data, and second, as a search solution where you use those core capabilities as building blocks to create tailored search applications. +You can think of {es} in two complementary ways: -### Data store and vector database use case +1. **As a datastore and vector database**: use {es} directly to ingest, store, and manage many types of data in a scalable, cost-efficient way, without the need to add anything else. +2. **As a foundation for custom applications**: including search and discovery experiences that you design and build using {es}'s building blocks. -All of the search capabilities you find on this page are possible because {{es}} is not just a search engine, but it’s also a scalable, cost-efficient [data store](/manage-data/data-store.md). -You can bring in many types of data, index them in near real time, and keep them stored in a way that makes them both searchable and analyzable. Common examples include, but are not limited to: +### Datastore and vector database -* **Textual data**: documents, logs, articles, or transcripts. -* **Numerical data**: metrics, performance data, sensor readings. -* **Geospatial data**: coordinates, maps, and location-based signals. -* **Vector data**: embeddings from {{ml}} models for semantic or hybrid search. +You can index many types of data, keep them stored efficiently, searchable, and analyzable. If all you need is a reliable and scalable datastore, you can use {es} that way without adding anything else. All of {es}’s advanced capabilities start with its role as a [data store](/manage-data/data-store.md). Examples include, but are not limited to: -By bringing all these capabilities together, Elasticsearch serves as a powerful data store, a geospatial search engine, a vector database, and more, all within a single technology. It forms the foundation of Elastic's unified data and search platform, enabling you to work with different data types seamlessly. To learn more, refer to the [{{es}} data store overview](/manage-data/data-store.md). +* **Textual data**: documents, logs, articles, or transcripts +* **Numerical data**: metrics, performance data, sensor readings +* **Time series data**: events, traces, or system metrics collected over time +* **Geospatial data**: coordinates, maps, and location-based signals +* **Vector data**: embeddings from {{ml}} models for semantic or hybrid search -### Search use case +By bringing these capabilities together, {es} acts as a powerful data store, time series database, geospatial engine, and vector database, all within a single technology. Whether you use it as a datastore or as the backbone for advanced search and analytics, this unified foundation enables you to work seamlessly with diverse data types and power your own applications. + +### Search and discovery applications + +Search is one of the common use cases built on {es}. With your own data (text, logs, metrics, events, vectors, or geospatial information), {es} gives you the tools to store, search, and analyze it. Using these building blocks, you can design search and discovery experiences, from internal knowledge bases to product catalogs, chat interfaces, or geospatial applications. + +{es} gives you the core platform to build the experiences that best match your requirements. -Think of {{es}} as a set of powerful building blocks. You bring in your own data, text, logs, metrics, events, vectors, or geospatial information, and {{es}} gives you the tools to store, search, and analyze it. By combining these capabilities, you can design and build the search and discovery experiences that fit your needs, from product catalogs to knowledge bases, chatbots, or geospatial applications. | Use case | Business goals | Technical requirements | | ------------------------------------ | ------------------------------------------------------------------ | ------------------------------------------------------------- | @@ -56,3 +63,10 @@ Think of {{es}} as a set of powerful building blocks. You bring in your own data | **Customer support search** | Surface relevant solutions, manage access controls, track metrics | Knowledge graph, role-based access, analytics | | **Chatbots/RAG** | Enable natural conversations, provide context, maintain knowledge | Vector search, ML models, knowledge base integration | | **Geospatial search** | Process location queries, sort by proximity, filter by area | Geo-mapping, spatial indexing, distance calculations | + +## Further reading + +* [{es} reference documentation](elasticsearch::docs/reference/elasticsearch/index.md) +* [The {es} data store](/manage-data/data-store.md) +* [Content connectors](elasticsearch::docs/reference/search-connectors/index.md) +* [{es} API documentation](https://www.elastic.co/docs/api/doc/elasticsearch/v9/) From ea10226b06bf80e0e0d75ef0d5d106daeec01f09 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Istv=C3=A1n=20Zolt=C3=A1n=20Szab=C3=B3?= Date: Wed, 17 Sep 2025 17:42:09 +0200 Subject: [PATCH 04/12] Fixes abbrevs. --- solutions/search.md | 29 ++++++++++++++--------------- 1 file changed, 14 insertions(+), 15 deletions(-) diff --git a/solutions/search.md b/solutions/search.md index d17c0564c8..b771a58d87 100644 --- a/solutions/search.md +++ b/solutions/search.md @@ -14,30 +14,30 @@ products: # The Elasticsearch solution -The {es} solution and serverless project type position {es} as a comprehensive platform: a scalable data store, a powerful search engine, and a vector database in one. At its core, {es} is a distributed datastore that can ingest, index, and manage various types of data in near real-time, making them both searchable and analyzable. With specialized user interfaces and tools, it provides the flexibility to create, deploy, and run a wide range of applications, from search to analytics to AI-driven solutions. +The {{es}} solution and serverless project type position {{es}} as a comprehensive platform: a scalable data store, a powerful search engine, and a vector database in one. At its core, {{es}} is a distributed datastore that can ingest, index, and manage various types of data in near real-time, making them both searchable and analyzable. With specialized user interfaces and tools, it provides the flexibility to create, deploy, and run a wide range of applications, from search to analytics to AI-driven solutions. -## What the {es} solution provides +## What the {{es}} solution provides -The {es} solution and serverless project type include specialized user interfaces and tools that simplify working with {es}: +The {{es}} solution and serverless project type include specialized user interfaces and tools that simplify working with {{es}}: * **Ingestion tools**: Content connectors, crawlers, file upload function, and indexing APIs for ingesting and storing data * **Data management and discovery**: Discover and Dashboards for exploring data, building visualizations, and creating interactive experiences * **Management interfaces**: Index Management and other tools for configuring and optimizing your stored data and implementation * **Search relevance tools**: Purpose-built UIs for managing synonyms, query rules, and other relevance-enhancing features * **AI toolkit**: RAG Playground and inference endpoints management for building AI-enhanced applications -* **Complete {es} REST API**: Full access to {es}'s comprehensive APIs for indexing, searching, and managing data +* **Complete {{es}} REST API**: Full access to {{es}}'s comprehensive APIs for indexing, searching, and managing data * **Deployment flexibility**: Run in Elastic Cloud, Elastic Serverless, or self-managed environments with consistent interfaces ## Core capabilities and use cases -You can think of {es} in two complementary ways: +You can think of {{es}} in two complementary ways: -1. **As a datastore and vector database**: use {es} directly to ingest, store, and manage many types of data in a scalable, cost-efficient way, without the need to add anything else. -2. **As a foundation for custom applications**: including search and discovery experiences that you design and build using {es}'s building blocks. +1. **As a datastore and vector database**: use {{es}} directly to ingest, store, and manage many types of data in a scalable, cost-efficient way, without the need to add anything else. +2. **As a foundation for custom applications**: including search and discovery experiences that you design and build using {{es}}'s building blocks. ### Datastore and vector database -You can index many types of data, keep them stored efficiently, searchable, and analyzable. If all you need is a reliable and scalable datastore, you can use {es} that way without adding anything else. All of {es}’s advanced capabilities start with its role as a [data store](/manage-data/data-store.md). Examples include, but are not limited to: +You can index many types of data, keep them stored efficiently, searchable, and analyzable. If all you need is a reliable and scalable datastore, you can use {{es}} that way without adding anything else. All of {{es}}’s advanced capabilities start with its role as a [data store](/manage-data/data-store.md). Examples include, but are not limited to: * **Textual data**: documents, logs, articles, or transcripts * **Numerical data**: metrics, performance data, sensor readings @@ -45,14 +45,13 @@ You can index many types of data, keep them stored efficiently, searchable, and * **Geospatial data**: coordinates, maps, and location-based signals * **Vector data**: embeddings from {{ml}} models for semantic or hybrid search -By bringing these capabilities together, {es} acts as a powerful data store, time series database, geospatial engine, and vector database, all within a single technology. Whether you use it as a datastore or as the backbone for advanced search and analytics, this unified foundation enables you to work seamlessly with diverse data types and power your own applications. +By bringing these capabilities together, {{es}} acts as a powerful data store, time series database, geospatial engine, and vector database, all within a single technology. Whether you use it as a datastore or as the backbone for advanced search and analytics, this unified foundation enables you to work seamlessly with diverse data types and power your own applications. ### Search and discovery applications -Search is one of the common use cases built on {es}. With your own data (text, logs, metrics, events, vectors, or geospatial information), {es} gives you the tools to store, search, and analyze it. Using these building blocks, you can design search and discovery experiences, from internal knowledge bases to product catalogs, chat interfaces, or geospatial applications. - -{es} gives you the core platform to build the experiences that best match your requirements. +Search is one of the common use cases built on {{es}}. With your own data (text, logs, metrics, events, vectors, or geospatial information), {{es}} gives you the tools to store, search, and analyze it. Using these building blocks, you can design search and discovery experiences, from internal knowledge bases to product catalogs, chat interfaces, or geospatial applications. +{{es}} gives you the core platform to build the experiences that best match your requirements. | Use case | Business goals | Technical requirements | | ------------------------------------ | ------------------------------------------------------------------ | ------------------------------------------------------------- | @@ -66,7 +65,7 @@ Search is one of the common use cases built on {es}. With your own data (text, l ## Further reading -* [{es} reference documentation](elasticsearch::docs/reference/elasticsearch/index.md) -* [The {es} data store](/manage-data/data-store.md) +* [{{es}} reference documentation](elasticsearch::docs/reference/elasticsearch/index.md) +* [The {{es}} data store](/manage-data/data-store.md) * [Content connectors](elasticsearch::docs/reference/search-connectors/index.md) -* [{es} API documentation](https://www.elastic.co/docs/api/doc/elasticsearch/v9/) +* [{{es}} API documentation](https://www.elastic.co/docs/api/doc/elasticsearch/v9/) From 4e7934fe00327b8d6d196d9e12ebccf149c1d8d3 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Istv=C3=A1n=20Zolt=C3=A1n=20Szab=C3=B3?= Date: Thu, 18 Sep 2025 11:26:41 +0200 Subject: [PATCH 05/12] Adds tip. --- solutions/search.md | 9 +++++++++ 1 file changed, 9 insertions(+) diff --git a/solutions/search.md b/solutions/search.md index b771a58d87..b54a222efa 100644 --- a/solutions/search.md +++ b/solutions/search.md @@ -69,3 +69,12 @@ Search is one of the common use cases built on {{es}}. With your own data (text, * [The {{es}} data store](/manage-data/data-store.md) * [Content connectors](elasticsearch::docs/reference/search-connectors/index.md) * [{{es}} API documentation](https://www.elastic.co/docs/api/doc/elasticsearch/v9/) + +::::{tip} +Considering whether {{es}} on {{serverless-full}} is the right deployment option for your needs? + +These resources can help you compare and decide: + +* [What’s different?](/deploy-manage/deploy/elastic-cloud/differences-from-other-elasticsearch-offerings.md): Understand the differences between {{serverless-full}} and other deployment types. +* [Billing](/deploy-manage/cloud-organization/billing/elasticsearch-billing-dimensions.md): Learn about the billing model for {{es}} on {{serverless-full}}. +:::: From f84813f64d11e9c9eadd2d0b743224d8c840fba9 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Istv=C3=A1n=20Zolt=C3=A1n=20Szab=C3=B3?= Date: Wed, 24 Sep 2025 17:01:17 +0200 Subject: [PATCH 06/12] Apply suggestion from @benironside Co-authored-by: Benjamin Ironside Goldstein <91905639+benironside@users.noreply.github.com> --- solutions/search.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/solutions/search.md b/solutions/search.md index b54a222efa..c7bda384fe 100644 --- a/solutions/search.md +++ b/solutions/search.md @@ -20,7 +20,7 @@ The {{es}} solution and serverless project type position {{es}} as a comprehensi The {{es}} solution and serverless project type include specialized user interfaces and tools that simplify working with {{es}}: -* **Ingestion tools**: Content connectors, crawlers, file upload function, and indexing APIs for ingesting and storing data +* **Ingestion tools**: Content connectors, crawlers, file upload capabilities, and indexing APIs for ingesting and storing data * **Data management and discovery**: Discover and Dashboards for exploring data, building visualizations, and creating interactive experiences * **Management interfaces**: Index Management and other tools for configuring and optimizing your stored data and implementation * **Search relevance tools**: Purpose-built UIs for managing synonyms, query rules, and other relevance-enhancing features From 109218033f166dba9fb920469ba4f1e41c02ba5f Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Istv=C3=A1n=20Zolt=C3=A1n=20Szab=C3=B3?= Date: Wed, 24 Sep 2025 17:01:43 +0200 Subject: [PATCH 07/12] Apply suggestion from @benironside Co-authored-by: Benjamin Ironside Goldstein <91905639+benironside@users.noreply.github.com> --- solutions/search.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/solutions/search.md b/solutions/search.md index c7bda384fe..8da2cbc140 100644 --- a/solutions/search.md +++ b/solutions/search.md @@ -33,7 +33,7 @@ The {{es}} solution and serverless project type include specialized user interfa You can think of {{es}} in two complementary ways: 1. **As a datastore and vector database**: use {{es}} directly to ingest, store, and manage many types of data in a scalable, cost-efficient way, without the need to add anything else. -2. **As a foundation for custom applications**: including search and discovery experiences that you design and build using {{es}}'s building blocks. +2. **As a foundation for custom applications**: use {{es}}'s building blocks to design and build applications including search and discovery tools. ### Datastore and vector database From dd9aaee59bef3311eb31d9c73017612fe87b7e60 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Istv=C3=A1n=20Zolt=C3=A1n=20Szab=C3=B3?= Date: Wed, 24 Sep 2025 17:02:25 +0200 Subject: [PATCH 08/12] Apply suggestion from @benironside Co-authored-by: Benjamin Ironside Goldstein <91905639+benironside@users.noreply.github.com> --- solutions/search.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/solutions/search.md b/solutions/search.md index 8da2cbc140..47b834a6e7 100644 --- a/solutions/search.md +++ b/solutions/search.md @@ -39,7 +39,7 @@ You can think of {{es}} in two complementary ways: You can index many types of data, keep them stored efficiently, searchable, and analyzable. If all you need is a reliable and scalable datastore, you can use {{es}} that way without adding anything else. All of {{es}}’s advanced capabilities start with its role as a [data store](/manage-data/data-store.md). Examples include, but are not limited to: -* **Textual data**: documents, logs, articles, or transcripts +* **Textual data**: documents, logs, articles, and transcripts * **Numerical data**: metrics, performance data, sensor readings * **Time series data**: events, traces, or system metrics collected over time * **Geospatial data**: coordinates, maps, and location-based signals From 77f6806610377caa6123abfbd6ca6c15f6fcf82e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Istv=C3=A1n=20Zolt=C3=A1n=20Szab=C3=B3?= Date: Wed, 24 Sep 2025 17:02:33 +0200 Subject: [PATCH 09/12] Apply suggestion from @benironside Co-authored-by: Benjamin Ironside Goldstein <91905639+benironside@users.noreply.github.com> --- solutions/search.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/solutions/search.md b/solutions/search.md index 47b834a6e7..7c7979ad8f 100644 --- a/solutions/search.md +++ b/solutions/search.md @@ -41,7 +41,7 @@ You can index many types of data, keep them stored efficiently, searchable, and * **Textual data**: documents, logs, articles, and transcripts * **Numerical data**: metrics, performance data, sensor readings -* **Time series data**: events, traces, or system metrics collected over time +* **Time series data**: events, traces, and system metrics collected over time * **Geospatial data**: coordinates, maps, and location-based signals * **Vector data**: embeddings from {{ml}} models for semantic or hybrid search From d40a69d9eb925557c914ce8c2fa61cb9ed1fa44b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Istv=C3=A1n=20Zolt=C3=A1n=20Szab=C3=B3?= Date: Wed, 24 Sep 2025 17:02:49 +0200 Subject: [PATCH 10/12] Apply suggestion from @benironside Co-authored-by: Benjamin Ironside Goldstein <91905639+benironside@users.noreply.github.com> --- solutions/search.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/solutions/search.md b/solutions/search.md index 7c7979ad8f..7b3e63e713 100644 --- a/solutions/search.md +++ b/solutions/search.md @@ -45,7 +45,7 @@ You can index many types of data, keep them stored efficiently, searchable, and * **Geospatial data**: coordinates, maps, and location-based signals * **Vector data**: embeddings from {{ml}} models for semantic or hybrid search -By bringing these capabilities together, {{es}} acts as a powerful data store, time series database, geospatial engine, and vector database, all within a single technology. Whether you use it as a datastore or as the backbone for advanced search and analytics, this unified foundation enables you to work seamlessly with diverse data types and power your own applications. +By bringing these capabilities together, {{es}} acts as a powerful data store, time series database, geospatial engine, and vector database, all within a single platform. Whether you use it as a datastore or as the backbone for advanced search and analytics, this unified foundation enables you to work seamlessly with diverse data types and power your own applications. ### Search and discovery applications From bea668dc75ef4283725ff4b6a834506e8802c3b5 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Istv=C3=A1n=20Zolt=C3=A1n=20Szab=C3=B3?= Date: Wed, 24 Sep 2025 17:09:11 +0200 Subject: [PATCH 11/12] Apply suggestion from @benironside Co-authored-by: Benjamin Ironside Goldstein <91905639+benironside@users.noreply.github.com> --- solutions/search.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/solutions/search.md b/solutions/search.md index 7b3e63e713..34dc0c3fc4 100644 --- a/solutions/search.md +++ b/solutions/search.md @@ -49,7 +49,7 @@ By bringing these capabilities together, {{es}} acts as a powerful data store, t ### Search and discovery applications -Search is one of the common use cases built on {{es}}. With your own data (text, logs, metrics, events, vectors, or geospatial information), {{es}} gives you the tools to store, search, and analyze it. Using these building blocks, you can design search and discovery experiences, from internal knowledge bases to product catalogs, chat interfaces, or geospatial applications. +Search is one of the common use cases built on {{es}}. {{es}} gives you the tools to store, search, and analyze your own data, including text, logs, metrics, events, vectors, and geospatial information. Using these building blocks, you can design search and discovery experiences, from internal knowledge bases to product catalogs, chat interfaces, or geospatial applications. {{es}} gives you the core platform to build the experiences that best match your requirements. From 67bcf8516652df0157f774fa755683d6410ed78c Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Istv=C3=A1n=20Zolt=C3=A1n=20Szab=C3=B3?= Date: Thu, 25 Sep 2025 17:40:36 +0200 Subject: [PATCH 12/12] Update solutions/search.md --- solutions/search.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/solutions/search.md b/solutions/search.md index 34dc0c3fc4..9ef3b0c07e 100644 --- a/solutions/search.md +++ b/solutions/search.md @@ -35,7 +35,7 @@ You can think of {{es}} in two complementary ways: 1. **As a datastore and vector database**: use {{es}} directly to ingest, store, and manage many types of data in a scalable, cost-efficient way, without the need to add anything else. 2. **As a foundation for custom applications**: use {{es}}'s building blocks to design and build applications including search and discovery tools. -### Datastore and vector database +### Datastore You can index many types of data, keep them stored efficiently, searchable, and analyzable. If all you need is a reliable and scalable datastore, you can use {{es}} that way without adding anything else. All of {{es}}’s advanced capabilities start with its role as a [data store](/manage-data/data-store.md). Examples include, but are not limited to: