Timeplus Enterprise 2.9

Each release of Timeplus Enterprise includes the following components:

• timeplusd: The core SQL engine
• timeplus_appserver: The application server providing web console access and REST API
• timeplus_web: The web console static resources. Starting from Timeplus Enterprise 2.9, this component is packaged into timeplus_appserver. No longer as a separate binary or container
• timeplus_connector: The service providing extra sources and sinks, managed by timeplus_appserver
• timeplus: The CLI (Command Line Interface) to start/stop/manage the deployment

Each component maintains its own version numbers. The version number for each Timeplus Enterprise release represents a verified combination of these components.

Key Highlights

Key highlights of the Timeplus 2.9 release include:

• Enhanced Mutable Streams: Introducing online schema evolution, versioning, coalesced storage, Time-To-Live (TTL), and secondary index management capabilities.
• Native JSON Support: A new native JSON data type and powerful json_encode / json_cast functions simplify working with JSON.
• Improved Data Integrity: Dead Letter Queue (DLQ) support for Materialized Views ensures robust data processing.
• Expanded Connectivity: Native HTTP External Stream for seamless integration with systems like Splunk, Elasticsearch, and more.
• Performance Boost: JIT (Just-In-Time) compilation for streaming queries delivers significant performance and efficiency improvements. Large cardinality sessionization.
• Parameterized Views: Create Parameterized Views for more flexible and reusable query patterns.
• Scalable Log Processing: Distributed LogStream enables efficient handling of large volumes of log data.
• Broader UDF Support: Python UDFs now run on ARM CPUs (Linux/macOS), and JavaScript UDFs benefit from multiple V8 instances.
• Refined Cluster UI: The web console offers an improved experience for visualizing and managing cluster nodes.

Supported OS

Deployment Type	OS
Linux bare metal	x64 or ARM chips: Ubuntu 20.04+, RHEL 8+, Fedora 35+, Amazon Linux 2023
Mac bare metal	Intel or Apple chips: macOS 14, macOS 15
Kubernetes	Kubernetes 1.25+, with Helm 3.12+

Releases

We recommend using stable releases for production deployment. Engineering builds are available for testing and evaluation purposes.

2.9.0 (Preview 3)

Released on 07-31-2025. Installation options:

• For Linux or Mac users: curl https://install.timeplus.com/2.9 | sh Downloads
• For Docker users (not recommended for production): docker run -p 8000:8000 docker.timeplus.com/timeplus/timeplus-enterprise:2.9.0-preview.3
• We will provide new Helm Charts for Kubernetes deployment when v2.9 is GA.

Component versions:

• timeplusd 2.9.9-rc.26
• timeplus_web 2.9.40
• timeplus_appserver 2.9.39
• timeplus_connector 2.9.1
• timeplus cli 2.9.0

Changelog

Compared to the 2.8.1 release:

• timeplusd 2.8.26 -> 2.9.9-rc.26
  • New Features:
    • Parameterized Views: You can now create parameterized views, allowing for more dynamic and reusable view definitions.
    • JIT Compilation for Queries: Introduced Just-In-Time (JIT) compilation for queries, potentially improving execution performance for certain query types.
    • New JSON Data Type & SQL Functions: Added a native JSON data type and SQL functions json_encode, json_cast, json_array_length, json_merge_patch for powerful JSON manipulation.
    • Mutable Stream TTL: You can now define Time-To-Live (TTL) for data in mutable streams, automatically managing data retention.
    • Materialized View DLQ: Introduced Dead Letter Queue (DLQ) support for materialized views to handle data processing errors more robustly.
    • HTTP External Stream: Added a new type of external stream to send streaming data to external HTTP endpoints, such as Splunk, Open Search and Slack.
    • MongoDB External Table: Added a new type of external table to send streaming data to MongoDB.
    • Enhanced MySQL External Table to support replace_query and on_duplicate_clause settings.
    • Enhanced Kafka External Stream and Pulsar External Stream to support write message headers via _tp_message_headers
    • Build and manage Alerts with SQL. Monitor your streaming data and automatically trigger actions when specific conditions are met.
    • Python UDFs on ARM: Python User-Defined Functions (UDFs) are now supported on ARM-based architectures (Linux/macOS), expanding platform compatibility.
    • Improved JavaScript UDFs: Enhanced JavaScript UDF execution with support for multiple V8 instances, improving concurrency and isolation (also available in 2.8.1 or above). JavaScript User Defined Aggregation Function supports null value as input.
    • Log Stream Virtual Columns: Log streams now include _filepath and _filename virtual columns, providing richer context about the data source.
    • UUID as Primary Key: Mutable streams now support the UUID data type for primary key columns.
    • Support SQL UDF on cluster. Support UUIDv7 functions
    • Initial version of CREATE TASK.
    • Initial version of CREATE NULL STREAM.
  • SQL and Data Model Enhancements:
    • Advanced EMIT Clause: The EMIT clause for changelog generation now supports EMIT ON UPDATE WITH DELAY and EMIT AFTER KEY EXPIRE options for more granular control over streaming results.
    • ALTER STREAM for Multiple Columns: You can now add or modify multiple columns in a single ALTER STREAM command.
    • Modifying Comments: Added ALTER COMMENT support for streams, views, materialized views, KVStreams, and RandomStreams.
    • Mutable Stream Schema Evolution: Support for adding new columns and dropping secondary indexes in mutable streams.
    • Support writing to nested array of records Avro schemas
    • Enhanced Kafka External Stream allows to customize the partitioner property, e.g. settings properties='partitioner=murmur2'
    • New query setting precise_float_parsing to precisely handle float numbers.
    • Added emit policy EMIT TIMEOUT and EMIT PER EVENT.
    • Added new functions array_partial_sort, array_partial_reverse_sort, and ulid_string_to_date_time.
  • Performance and Scalability:
    • Incremental Checkpointing: Implemented and enabled incremental checkpointing by default for substreams, hybrid hash joins, and Materialized Views, significantly reducing recovery time and resource usage during stateful operations.
    • Optimized Connection Pooling: Refactored internal connection pooling for improved performance and resource management.
    • Parallel Log Processing: Log files from sources can now be processed in parallel for faster data ingestion.
    • Coalesced Mutable Streams: Introduced coalesced mutable streams for optimized storage and querying of updatable data.
    • Distributed LogStream: Enhanced LogStream capabilities for distributed environments, improving scalability for log data processing.
  • Monitoring and Management:
    • New System Views: Introduced additional built-in system views (e.g., for troubleshooting distributed queries, MVs, query memory, and checkpoint status) for enhanced system observability.
    • Versioned SHOW CREATE: The SHOW CREATE command now displays multi-versioned definitions for streams, views, MVs, UDFs, format schemas, and databases, aiding in tracking changes.
    • Disk Metrics for Dictionaries: Added metrics to monitor disk size usage by dictionaries.
    • MV Node Pinning & Placement: Added functionality to pin materialized view execution to specific cluster nodes and manage node placements for better resource control.
    • Kafka External Stream Timeout: Added connection_timeout_ms setting for Kafka external streams.
    • Dependency Checks for Storage Policies: Added checks for dependencies before allowing a storage policy or disk to be dropped.
    • A set of views are provided in the system namespace that enable effective troubleshooting and monitoring of your streaming data operations
  • External Data Integration:
    • Kafka Enhancements: Added support for writing Kafka message timestamps and improved error handling for Kafka external streams with _tp_time and CSV format.
    • Iceberg Integration: Provided various bug fixes and enhancements for interacting with Apache Iceberg tables.
    • Pulsar Client Upgrade: Upgraded the Pulsar C++ client to version 3.7.0.
  • Security Enhancements:
    • Improved mechanisms for password propagation within clustered environments.
    • Support for utilizing user information from HTTP URL parameters for authentication or context.
• timeplus_web 2.8.8 -> 2.9.40
  • UI/UX Enhancements:
    • New Log Viewer: Introduced a significantly improved log viewer with enhanced filtering capabilities, better timeline interactions, improved tooltip displays, and refined time range calculations.
    • Database Selector: Improved the database selector in the UI, including dimming databases without resources and separating system databases for better clarity.
    • Data Lineage: Enhanced data lineage visualization to display nodes from other databases.
    • Timezone Persistence: User-selected timezone preferences are now persisted in local storage for a consistent experience.
    • Improved layout for HTTP source creation and other external stream Guided Data Ingestion (GDI) UIs.
    • SQL Query: side panel is simplified by removing the snippets and functions accordion, long SQL statement is wrapped by default, cursor position is kept when you switch pages or tabs.
  • Resource Management (Streams, MVs, Views, UDFs):
    • Replaced the Redpanda-Connect based HTTP sink and Slack sink with the new HTTP External Stream in the core engine.
    • Materialized Views (MVs):
      • Added UI support for pausing and resuming materialized views.
      • Introduced Dead Letter Queue (DLQ) support and UI for MVs.
      • Improved MV details page, monitoring, and statistics display.
      • Enabled modifying comments for MVs via DDL.
      • Added ability to inspect MV status data by navigating to the query page.
      • Moved the "Pause" button to the detailed page.
    • Streams:
      • Improved Stream details page.
      • Enabled modifying comments for streams via DDL.
      • Added definition view to external streams and external tables in the side panel.
    • User-Defined Functions (UDFs):
      • Added UI for creating JavaScript UDFs using DDL.
      • Provided code templates for JavaScript and Python UDFs.
    • External Streams: Added UI support for creating HTTP external streams.
  • Cluster Management:
    • Improved Cluster Details Page: Enhanced the cluster details page with a top statistics bar, better data presentation, and improved node details view.
    • Enhanced cluster data generation and retrieval for UI display.
    • Added the log view to the node page
  • Removed the previous Redpanda Connect based alerts and replaced it with the new Alerts feature, which allows you to create alerts using SQL queries.
• timeplus_appserver 2.8.6 -> 2.9.39
  • Serves the updated Timeplus Web Console static files.
  • Added backend support for new external table types including MySQL, PostgreSQL, and Iceberg.
  • Upgraded the proton-go-driver from v2.0.19 to v2.1.2 to support new json data type and various bug fixes.
  • New REST API for pipeline management.
  • Improved the performance of checking statistics for materialized views and streams.
  • Removed the previous Redpanda Connect based alerts and replaced it with the new Alerts feature, which allows you to create alerts using SQL queries.
  • On data lineage, show the last 1 minute metrics, instead of the last 30 minutes.
• timeplus_connector 2.2.8 -> 2.9.1
  • removed the support for internal k/v service, since metadata is saved in mutable streams in v2.9
  • Upgraded the proton-go-driver from v2.0.19 to v2.1.2 to support new json data type and various bug fixes.
• timeplus cli 2.8.0 -> 2.9.0
  • No longer need to start/stop the timeplus_web component.
  • Load timeplus_connector.yaml from the relative path or via BENTHOS_CONFIG_PATH environment variable.

Upgrade Instructions:

If you install Timeplus Enterprise 2.7 or earlier, the metadata for the Redpanda Connect sources and sinks are saved in a special key/value service. v2.8 switches to mutable streams for such metadata by default and provides a migration tool. In 2.9, all metadata are saved in mutable streams and the previous key/value service has been removed. Please upgrade to 2.8 first if you are on 2.7 or earlier. Then upgrade to 2.9.

Known issues

1. Direct upgrades from version 2.3 or earlier are not supported. Please perform a clean installation of 2.9.x and utilize timeplus sync CLI or Timeplus External Stream for data migration.
2. For existing deployments with any version from 2.3 to 2.7, please upgrade to 2.8 first and migrate the metadata. .
3. Pulsar external stream functionality is limited to Linux bare metal builds and Linux-based Docker images, excluding macOS bare metal builds.
4. The timeplus_connector component may experience health issues on Ubuntu Linux with x86_64 chips, affecting Redpanda Connect functionality. This issue is specific to Ubuntu and does not affect other Linux distributions.