AUTO: Sync ScalarDB docs in English to docs site repo (#1426)

Co-authored-by: josh-wong <[email protected]>

Author: github-actions[bot]

versioned_docs/version-3.13/roadmap.mdx

@@ -18,85 +18,73 @@ If you have a feature request or want to prioritize feature development, please
 
 :::
 
-
-### CY2025 Q2
-
+### CY2025 Q3
 
 #### Support for additional databases
 
-- **IBM Db2**
-    - Users will be able to use IBM Db2 as an underlying database through ScalarDB Cluster.
 - **TiDB**
-    - Users will be able to use TiDB as an underlying database through ScalarDB Cluster.
-- **Databricks**
-    - Users will be able to use Databricks as an underlying database through ScalarDB Cluster and ScalarDB Analytics.
-- **Snowflake**
-    - Users will be able to use Snowflake as an underlying database through ScalarDB Cluster and ScalarDB Analytics.
+    - Users will be able to use TiDB as an underlying database through ScalarDB Core and ScalarDB Cluster.
+- **AlloyDB**
+    - Users will be able to use AlloyDB as an underlying database through ScalarDB Core and ScalarDB Cluster.
+- **Spanner**
+    - Users will be able to use Spanner as an underlying database through ScalarDB Core and ScalarDB Cluster.
 
-#### Usability
+#### New features
 
-- **Addition of decimal data types**
-    - Users will be able to use decimal data types so that users can handle decimal numbers with high precision.
-- **Removal of extra-write strategy**
-    - Users will no longer be able to use the extra-write strategy to make transactions serializable. Although ScalarDB currently provides two strategies (extra-read and extra-write strategies) to make transactions serializable, the extra-write strategy has several limitations. For example, users can't issue write and scan operations in the same transaction. Therefore, the strategy will be removed so that users don't need to worry about such limitations when creating applications.
-- **Better governance in ScalarDB Analytics**
-    - Users will be able to be authenticated and authorized by using the ScalarDB Core features.
+- **Decoupled metadata management**
+    - Users will be able to start using ScalarDB Cluster without migrating or changing the schemas of existing applications by managing the transaction metadata of ScalarDB in a separate location.
+- **Role-based access control (RBAC)**
+    - Users will be able to define roles and assign permissions to those roles so that users can manage access control in a more flexible way.
+- **Views**
+    - Users will be able to define views so that they can manage multiple different databases in an easier and simplified way.
+- **Addition of SQL operations for aggregation**
+    - Users will be able to issue aggregation operations in ScalarDB SQL.
+- **Universal catalog**
+    - Users will be able to manage metadata, including schemas and semantic information, for operational and analytical databases across separate business domains in a unified manner.
+- **Universal authentication and authorization**
+    - Users will be able to be given access to ScalarDB Cluster and ScalarDB Analytics by using a unified authentication and authorization method.
 
-#### Performance
+#### Improvements
 
-- **Addition of read-committed isolation**
-    - Users will be able to run transactions with a read-committed isolation to achieve better performance for applications that do not require strong correctness.
-- **One-phase commit optimization**
-    - Users will be able to run a transaction more efficiently by using one-phase commit if the operations of the transaction are all applied to a single database or a single partition.
-- **Optimization for multiple write operations per database**
-    - Users will be able to run transactions more efficiently with a batch preparation and commitment if there are multiple write operations for a database.
-- **Optimization for read-only transactions**
-    - Users will be able to run transactions more efficiently by avoiding coordinator writes when committing transactions.
-- **Removal of WAL-interpreted views in ScalarDB Analytics**
-    - Users will be able to read committed data by using ScalarDB Core instead of WAL-interpreted views, which will increase query performance.
+- **Increased BLOB type size for Oracle Database and IBM Db2**
+    - Users will be able to use larger BLOB type size in ScalarDB Core and ScalarDB Cluster. The maximum size of the BLOB type will be increased to 4 GB.
+
+#### Usability
+
+- **More flexible ALTER operations**
+    - Users will be able to issue more flexible ALTER operations, such as altering schemas, renaming namespaces/tables/columns, and dropping columns, so that they can manage their schemas in a more flexible way.
 
 #### Cloud support
 
-- **Container offering in Azure Marketplace for ScalarDB Cluster**
-    - Users will be able to deploy ScalarDB Cluster by using the Azure container offering, which enables users to use a pay-as-you-go subscription model.
 - **Google Cloud Platform (GCP) support for ScalarDB Cluster**
     - Users will be able to deploy ScalarDB Cluster in Google Kubernetes Engine (GKE) in GCP.
 - **Container offering in Amazon Marketplace for ScalarDB Analytics**
     - Users will be able to deploy ScalarDB Analytics by using the container offering, which enables users to use a pay-as-you-go subscription model.
+- **Red Hat OpenShift support**
+    - Users will be able to use Red Hat–certified Helm Charts for ScalarDB Cluster in OpenShift environments.
 
-### CY2025 Q3
-
-#### New capabilities
-
-- **Decoupled metadata management**
-    - Users will be able to start using ScalarDB Cluster without migrating or changing the schemas of existing applications by managing the transaction metadata of ScalarDB in a separate location.
-
-#### Usability
-
-- **Views**
-  - Users will be able to define views so that they can manage multiple different databases in an easier and simplified way.
-- **Addition of SQL operations for aggregation**
-    - Users will be able to issue aggregation operations in ScalarDB SQL.
-- **Elimination of out-of-memory errors due to large scans**
-    - Users will be able to issue large scans without experiencing out-of-memory errors.
-- **Enabling of read operations during a paused duration**
-    - Users will be able to issue read operations even during a paused duration so that users can still read data while taking backups.
-
-#### Scalability and availability
+#### AI/LLM support
 
-- **Semi-synchronous replication**
-    - Users will be able to replicate the data of ScalarDB-based applications in a disaster-recoverable manner. For example, assume you provide a primary service in Tokyo and a standby service in Osaka. In case of catastrophic failure in Tokyo, you can switch the primary service to Osaka so that you can continue to provide the service without data loss and extended downtime.
+- **Model Context Protocol (MCP) server**
+    - Users will be able to use the MCP server of ScalarDB Core and ScalarDB Cluster to interact with them by using AI and large language model (LLM) applications. The MCP server will provide a way to communicate with ScalarDB by using natural language, enabling users to perform operations like querying and managing data in a more intuitive manner.
+- **LLM-friendly rule files for ScalarDB**
+    - Users will be able to ask questions and tasks to LLMs by using the LLM-friendly rule files so that LLMs can work for them with better understanding of ScalarDB. The rule files will be designed to provide LLMs with the necessary context and instructions to effectively interact with ScalarDB, making it easier for users to leverage AI capabilities in their applications.
 
 ### CY2025 Q4
 
-#### New capabilities
+#### New features
 
 - **Native secondary index**
     - Users will be able to define flexible secondary indexes. The existing secondary index is limited because it is implemented based on the common capabilities of the supported databases' secondary indexes. Therefore, for example, you cannot define a multi-column index. The new secondary index will be created at the ScalarDB layer so that you can create more flexible indexes, like a multi-column index.
-- **Universal catalog**
-    - Users will be able to manage metadata, including schemas and semantic information, for operational and analytical databases across separate business domains in a unified manner.
-- **Universal authentication and authorization**
-    - Users will be able to be given access to ScalarDB Cluster and ScalarDB Analytics by using a unified authentication and authorization method.
+- **Two-layered query engines**
+    - Users will be able to use two-layered query engines to better federate analytical queries across domains. The first-layer query engine is responsible for federating analytical queries across various domains, while the second-layer query engine federates analytical queries within a specific domain across its corresponding databases.
+
+#### Usability
+
+- **Addition of decimal data types**
+    - Users will be able to use decimal data types so that users can handle decimal numbers with high precision.
+- **Elimination of out-of-memory errors due to large scans**
+    - Users will be able to issue large scans without experiencing out-of-memory errors.
 
 #### Support for additional databases (object storage)
 
@@ -114,8 +102,8 @@ If you have a feature request or want to prioritize feature development, please
 
 #### Cloud support
 
-- **Red Hat OpenShift support**
-    - Users will be able to use Red Hat–certified Helm Charts for ScalarDB Cluster in OpenShift environments.
+- **Container offering in Azure Marketplace for ScalarDB Cluster**
+    - Users will be able to deploy ScalarDB Cluster by using the Azure container offering, which enables users to use a pay-as-you-go subscription model.
 - **Container offering in Google Cloud Marketplace**
     - Users will be able to deploy ScalarDB Cluster by using the Google Cloud container offering, which enables users to use a pay-as-you-go subscription model.