Changelog

All the latest features and updates to Timescale products.

SQL Assistant uses AI to help you write SQL faster and more accurately.

• Real-time help: chat with models like OpenAI 4o and Claude 3.5 Sonnet to get help writing SQL. Describe what you want in natural language and have AI write the SQL for you.

• Error resolution: when you run into an error, SQL Assistant proposes a recommended fix that you can choose to accept.

  

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• Generate titles and descriptions: click a button and SQL Assistant generates a title and description for your query. No more untitled queries!

  

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See our blog post or docs for full details!

Starting this week, all new services created on Timescale Cloud use TimescaleDB v2.17. Existing services are upgraded gradually during their maintenance windows.

TimescaleDB v2.17 significantly improves the performance of continuous aggregate refreshes, and contains performance improvements for analytical queries and delete operations over compressed hypertables.

Best practice is to upgrade at the next available opportunity.

Highlighted features in TimescaleDB v2.17 are:

• Significant performance improvements for continuous aggregate policies:

  • Continuous aggregate refresh now uses merge instead of deleting old materialized data and re-inserting.

  • Continuous aggregate policies are now more lightweight, use less system resources, and complete faster. This update:

    • Decreases dramatically the amount of data that must be written on the continuous aggregate in the presence of a small number of changes
    • Reduces the i/o cost of refreshing a continuous aggregate
    • Generates fewer Write-Ahead Logs (WAL)

• Increased performance for real-time analytical queries over compressed hypertables:

  • We are excited to introduce additional Single Instruction, Multiple Data (SIMD) vectorization optimization to TimescaleDB. This release supports vectorized execution for queries that group by using the segment_by column(s), and aggregate using the sum, count, avg, min, and max basic aggregate functions.

  • Stay tuned for more to come in follow-up releases! Support for grouping on additional columns, filtered aggregation, vectorized expressions, and time_bucket is coming soon.

  • Improved performance of deletes on compressed hypertables when a large amount of data is affected.

    This improvement speeds up operations that delete whole segments by skipping the decompression step. It is enabled for all deletes that filter by the segment_by column(s).

TimescaleDB introduces essential updates to facilitate Health Insurance Portability and Accountability Act (HIPAA) compliance, empowering organizations to better protect sensitive healthcare information while simplifying regulatory adherence. Best practice is that customers upgrade to the Enterprise plan to leverage the following improvements in data security and auditing:

• Introduced enhanced encryption and access controls: Timescale encrypts all data at rest and in transit, while providing SAML, SSO, and MFA options for added access security.
• Expanded audit logging for HIPAA compliance: with the pgAudit and pgSodium extensions, you gain comprehensive logging for key data interactions. This enables you to capture the following information: user identity, access times, types of operations, and specific data accessed. You use these logs to identify and investigate potential security incidents.
• Established breach notification protocol: in case of a PHI data breach, Timescale notifies affected customers within 72 hours, ensuring transparency and compliance with HIPAA requirements.

Highlighted features in this release:

• Robust auditing capabilities: Timescale Cloud now enables the pgAudit extension and soon, the pgSodium extension, providing essential logging capabilities to support HIPAA audits. By capturing actions such as read, write, and delete on sensitive data, these logs help users monitor and investigate access to PHI as required by HIPAA.
• Detailed compliance documentation: For customers needing additional verification of security practices, Timescale now offers a Business Associate Agreement (BAA) and a HIPAA Security Rule Self-Assessment, in addition to SOC 2 Type II and GDPR compliance documentation.
• Shared responsibility model for compliance: Timescale's shared responsibility model clarifies roles between Timescale and customers, outlining each party's duties in data encryption, access management, auditing, and breach notification.

Customers can now access more than just the most recent 500 logs within the Timescale Console. We've updated the user experience, including scrollbar with infinite scrolling capabilities.

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We've added instructions for connecting to Timescale using your .NET workflow. In Console after service creation, or in the Actions tab, you can now select .NET from the developer library list. The guide demonstrates how to use Npgsql to integrate Timescale with your existing software stack.

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In the Jobs section of the Explorer, users can now see the status (completed/failed) of the last 5 runs of each job.

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This early access feature enables you to automatically create, update, and maintain embeddings as your data changes. Just like an index, Timescale handles all the complexity: syncing, versioning, and cleanup happen automatically. This means no manual tracking, zero maintenance burden, and the freedom to rapidly experiment with different embedding models and chunking strategies without building new pipelines. Navigate to the AI tab in your service overview and follow the instructions to add your OpenAI API key and set up your first vectorizer or read our guide to automate embedding generation with pgai Vectorizer for more details.

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Fetch and query data from multiple PostgreSQL databases, including time-series data in hypertables, directly within Timescale Cloud using foreign data wrappers (FDW). No more complicated ETL processes or external tools—just seamless integration right within your SQL editor. This feature is ideal for developers who manage multiple PostgreSQL and time-series instances and need quick, easy access to data across databases.

This release adds support for runtime chunk exclusion for queries that need to access tiered storage. Chunk exclusion now works with queries that use stable expressions in the WHERE clause. The most common form of this type of query is:

SELECT * FROM  hypertable WHERE timestamp_col > now() - '100 days'::interval

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For more info on queries with immutable/stable/volatile filters, check our blog post on Implementing constraint exclusion for faster query performance.

If you no longer want to use tiered storage for a particular hypertable, you can now disable tiering and drop the associated tiering metadata on the hypertable with a call to disable_tiering function.

Timescale Console now shows recommendations for services with too many small chunks in their hypertables. Recommendations for new intervals that improve service performance are displayed for each underperforming service and hypertable. Users can then change their chunk interval and boost performance within Timescale Console.

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After creating a service, users can now create a hypertable directly in Timescale Console by first creating a table, then converting it into a hypertable. This is possible using the in-console SQL editor. All standard hypertable configuration options are supported, along with any customization of the underlying table schema.

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The newest version of Data Mode Notebooks is now waaaay faster. Why? We've incorporated the newly developed v3 of our query engine that currently powers Timescale Console's SQL Editor. Check out the difference in query response times.

Last year, we began developing a solution for low-downtime migration from PostgreSQL and TimescaleDB. Since then, this solution has evolved significantly, featuring enhanced functionality, improved reliability, and performance optimizations. We're now proud to announce that live migration is production-ready with the release of version 1.0.

Many of our customers have successfully migrated databases to Timescale using live migration, with some databases as large as a few terabytes in size.

As part of the service creation flow, we offer the following:

• Connect to services from different sources
• Import and migrate data from various sources
• Create hypertables

Previously, these actions were only visible during the service creation process and couldn't be accessed later. Now, these actions are persisted within the service, allowing users to leverage them on-demand whenever they're ready to perform these tasks.

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We've noticed users struggling to convert their MySQL schema and data into their Timescale Cloud services. This was due to the semantic differences between MySQL and PostgreSQL. To simplify this process, we now offer easy-to-follow instructions to import data from MySQL to Timescale Cloud. This feature is available as part of the data import wizard, under the Import from MySQL option.

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In Timescale Console, we offer the SQL editor so you can directly querying your service. As a new improvement, if a query is waiting on locks and can't complete execution, Timescale Console now displays the current lock contention in the results section .

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Timescale now supports multiple CIDRs on the customer VPC. Customers who want to take advantage of multiple CIDRs will need to recreate their peering.

We've been listening to your feedback and noticed that Timescale Console users have diverse needs. Some of you are focused on operational tasks like adding replicas or changing parameters, while others are diving deep into data analysis to gather insights.

To better serve you, we've introduced new modes to the Timescale Console UI—tailoring the experience based on what you're trying to accomplish.

Ops mode is where you can manage your services, add replicas, configure compression, change parameters, and so on.

Data mode is the full PopSQL experience: write queries with autocomplete, visualize data with charts and dashboards, schedule queries and dashboards to create alerts or recurring reports, share queries and dashboards, and more.

Try it today and let us know what you think!

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Now users can upload from Parquet to Timescale Cloud by uploading the file from their local file system. For files larger than 250 MB, or if you want to do it yourself, follow the three-step process to upload Parquet files to Timescale.

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• In the Ops mode SQL editor, you can now highlight a statement to run a specific statement.

Scale and Enterprise customers can now configure two new multiple high availability (HA) replica options directly through Timescale Console:

• Two HA replicas (both asynchronous) - our highest availability configuration.
• Two HA replicas (one asynchronous, one synchronous) - our highest data integrity configuration.

Previously, Timescale offered only a single synchronous replica for customers seeking high availability. The single HA option is still available.

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For more details on multiple HA replicas, see Manage high availability.

• In the Console SQL editor, we now indicate if your database session is healthy or has been disconnected. If it's been disconnected, the session will reconnect on your next query execution.

  

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• Released live-migration v0.0.26 and then v0.0.27 which includes multiple performance improvements and bugfixes as well as better support for PostgreSQL 12.

Now you can simply click to run SQL statements in various places in the Console. This requires that the SQL Editor is enabled for the service.

• Enable Continuous Aggregates from the CAGGs wizard by clicking Run below the SQL statement.

  

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• Enable database extensions by clicking Run below the SQL statement.

  

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• Query data instantly with a single click in the Console after successfully uploading a CSV file.

  

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Last week we announced the new in-console SQL editor. However, there was a limitation where a new database session was created for each query execution.

Today we removed that limitation and added support for keeping one database session for each user logged in, which means you can do things like start transactions:

begin;
insert into users (name, email) values ('john doe', 'john@example.com');
abort; -- nothing inserted

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Or work with temporary tables:

create temporary table temp_users (email text);
insert into temp_sales (email) values ('john@example.com');
-- table will automatically disappear after your session ends

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Or use the set command:

set search_path to 'myschema', 'public';

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We've added a new tab to the service screen that allows users to query their database directly, without having to leave the console interface.

• For existing services on Timescale, this is an opt-in feature. For all newly created services, the SQL Editor will be enabled by default.
• Users can disable the SQL Editor at any time by toggling the option under the Operations tab.
• The editor supports all DML and DDL operations (any single-statement SQL query), but doesn't support multiple SQL statements in a single query.

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After service creation, we now offer a dedicated section for data import, including options to import from Postgres as a source or from CSV files.

The enhanced Postgres import instructions now offer several options: single table import, schema-only import, partial data import (allowing selection of a specific time range), and complete database import. Users can execute any of these data imports with just one or two simple commands provided in the data import section.

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We've released v0.0.25 of Live migration that includes the following improvements:

• Support migrating tsdb on non public schema to public schema
• Pre-migration compatibility checks
• Docker compose build fixes

We have added a CSV import tool to the Timescale Console. For all TimescaleDB services, after service creation you can:

• Choose a local file
• Select the name of the data collection to be uploaded (default is file name)
• Choose data types for each column
• Upload the file as a new hypertable within your service Look for the Import data from .csv tile in the Import your data step of service creation.

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Customers now have more visibility into the state of replicas running on Timescale Cloud. We’ve released a new parameter called Replica Lag within the Service Overview for both Read and High Availability Replicas. Replica lag is measured in bytes against the current state of the primary database. For questions or concerns about the relative lag state of your replica, reach out to Customer Support.

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Customers can now adjust their chunk interval for their hypertables and continuous aggregates through the Timescale UI. In the Explorer, select the corresponding hypertable you would like to adjust the chunk interval for. Under Chunk information, you can change the chunk interval. Note that this only changes the chunk interval going forward, and does not retroactively change existing chunks.

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We've released permission granting via role assumption to CloudWatch. Role assumption is both more secure and more convenient for customers who no longer need to rotate credentials and update their exporter config.

For more details take a look at our documentation.

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We’ve added a 2FA status column to the Members page, allowing customers to easily see whether each project member has 2FA enabled or disabled.

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The pgai extension v0.3.0 now supports embedding creation and LLM reasoning using models from Anthropic and Cohere. For details and examples, see this post for pgai and Cohere, and this post for pgai and Anthropic.

pgvectorscale extension v0.3.0 adds support for ARM processors and improves recall when using StreamingDiskANN indexes with low dimensionality vectors. We recommend updating to this version if you are self-hosting.

TimescaleDB v2.16.0 contains significant performance improvements when working with compressed data, extended join support in continuous aggregates, and the ability to define foreign keys from regular tables towards hypertables. We recommend upgrading at the next available opportunity.

Any new service created on Timescale Cloud starting today uses TimescaleDB v2.16.0.

In TimescaleDB v2.16.0 we:

• Introduced multiple performance focused optimizations for data manipulation operations (DML) over compressed chunks.

  Improved upsert performance by more than 100x in some cases and more than 500x in some update/delete scenarios.

• Added the ability to define chunk skipping indexes on non-partitioning columns of compressed hypertables.

  TimescaleDB v2.16.0 extends chunk exclusion to use these skipping (sparse) indexes when queries filter on the relevant columns, and prune chunks that do not include any relevant data for calculating the query response.

• Offered new options for use cases that require foreign keys defined.

  You can now add foreign keys from regular tables towards hypertables. We have also removed some really annoying locks in the reverse direction that blocked access to referenced tables while compression was running.

• Extended Continuous Aggregates to support more types of analytical queries.

  More types of joins are supported, additional equality operators on join clauses, and support for joins between multiple regular tables.

Highlighted features in this release

• Improved query performance through chunk exclusion on compressed hypertables.

  You can now define chunk skipping indexes on compressed chunks for any column with one of the following integer data types: smallint, int, bigint, serial, bigserial, date, timestamp, timestamptz.

  After calling enable_chunk_skipping on a column, TimescaleDB tracks the min and max values for that column, using this information to exclude chunks for queries filtering on that column, where no data would be found.

• Improved upsert performance on compressed hypertables.

  By using index scans to verify constraints during inserts on compressed chunks, TimescaleDB speeds up some ON CONFLICT clauses by more than 100x.

• Improved performance of updates, deletes, and inserts on compressed hypertables.

  By filtering data while accessing the compressed data and before decompressing, TimescaleDB has improved performance for updates and deletes on all types of compressed chunks, as well as inserts into compressed chunks with unique constraints.

  By signaling constraint violations without decompressing, or decompressing only when matching records are found in the case of updates, deletes and upserts, TimescaleDB v2.16.0 speeds up those operations more than 1000x in some update/delete scenarios, and 10x for upserts.

• You can add foreign keys from regular tables to hypertables, with support for all types of cascading options. This is useful for hypertables that partition using sequential IDs, and need to reference these IDs from other tables.

• Lower locking requirements during compression for hypertables with foreign keys

  Advanced foreign key handling removes the need for locking referenced tables when new chunks are compressed. DML is no longer blocked on referenced tables while compression runs on a hypertable.

• Improved support for queries on Continuous Aggregates

  INNER/LEFT and LATERAL joins are now supported. Plus, you can now join with multiple regular tables, and have more than one equality operator on join clauses.

PostgreSQL 13 support removal announcement

Following the deprecation announcement for PostgreSQL 13 in TimescaleDB v2.13, PostgreSQL 13 is no longer supported in TimescaleDB v2.16.

The currently supported PostgreSQL major versions are 14, 15, and 16.

To support evolving customer needs, Timescale Cloud now offers three plans to provide more value, flexibility, and efficiency.

• Performance: for cost-focused, smaller projects. No credit card required to start.
• Scale: for developers handling critical and demanding apps.
• Enterprise: for enterprises with mission-critical apps.

Each plan continues to bill based on hourly usage, primarily for compute you run and storage you consume. You can upgrade or downgrade between Performance and Scale plans via the Console UI at any time. More information about the specifics and differences between these pricing plans can be found here in the docs.

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The individual tiles on the services page have been enhanced with new information, including high-availability status. This will let you better assess the state of your services at a glance.

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Improvements:

• Automatic retries are now available for the initial data copy of the migration
• Now uses pgcopydb for initial data copy for PG to TSDB migrations also (already did for TS to TS) which has a significant performance boost.
• Fixes issues with TimescaleDB v2.13.x migrations
• Support for chunk mapping for hypertables with custom schema and table prefixes

The following improvements have been made to Timescale products:

• Timescale Cloud:

  • The connection pooler has been updated and now avoids multiple reloads
  • The tsdbadmin user can now grant the following roles to other users: pg_checkpoint,pg_monitor,pg_signal_backend,pg_read_all_stats,pg_stat_scan_tables
  • Timescale Console is far more reliable.

• TimescaleDB

  • The TimescaleDB v2.15.3 patch release improves handling of multiple unique indexes in a compressed INSERT, removes the recheck of ORDER when querying compressed data, improves memory management in DML functions, improves the tuple lock acquisition for tiered chunks on replicas, and fixes an issue with ORDER BY/GROUP BY in our HashAggregate optimization on PG16. For more information, see the release note.
  • The TimescaleDB v2.15.2 patch release improves sort pushdown for partially compressed chunks, and compress_chunk with a primary space partition. The metadata function is removed from the update script, and hash partitioning on a primary column is disallowed. For more information, see the release note.

The following improvements have been made to the Timescale live-migration docker image:

• Table-based filtering is now available during live migration.
• Improvements to pbcopydb increase performance and remove unhelpful warning messages.
• The user notification log enables you to always select the most recent release for a migration run.

For improved stability and new features, update to the latest timescale/live-migration docker image. To learn more, see the live migration docs.

Ollama is now integrated with pgai.

Ollama is the easiest and most popular way to get up and running with open-source language models. Think of Ollama as Docker for LLMs, enabling easy access and usage of a variety of open-source models like Llama 3, Mistral, Phi 3, Gemma, and more.

With the pgai extension integrated in your database, embed Ollama AI into your app using SQL. For example:

select ollama_generate
( 'llava:7b'
, 'Please describe this image.'
, _images=> array[pg_read_binary_file('/pgai/tests/postgresql-vs-pinecone.jpg')]
, _system=>'you are a helpful assistant'
, _options=> jsonb_build_object
  ( 'seed', 42
  , 'temperature', 0.9
  )
)->>'response'
;

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To learn more, see the pgai Ollama documentation.

The compression wizard is now available on Timescale Cloud. Select a hypertable and be guided through enabling compression through the UI!

To access the compression wizard, navigate to Explorer, and select the hypertable you would like to compress. In the top right corner, hover where it says Compression off, and open the wizard. You will then be guided through the process of configuring compression for your hypertable, and can compress it directly through the UI.

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The vectorscale extension is now available on Timescale Cloud.

pgvectorscale complements pgvector, the open-source vector data extension for PostgreSQL, and introduces the following key innovations for pgvector data:

• A new index type called StreamingDiskANN, inspired by the DiskANN algorithm, based on research from Microsoft.
• Statistical Binary Quantization: developed by Timescale researchers, This compression method improves on standard Binary Quantization.

On benchmark dataset of 50 million Cohere embeddings (768 dimensions each), PostgreSQL with pgvector and pgvectorscale achieves 28x lower p95 latency and 16x higher query throughput compared to Pinecone's storage optimized (s1) index for approximate nearest neighbor queries at 99% recall, all at 75% less cost when self-hosted on AWS EC2.

To learn more, see the pgvectorscale documentation.

The pgai extension is now available on Timescale Cloud.

pgai brings embedding and generation AI models closer to the database. With pgai, you can now do the following directly from within PostgreSQL in a SQL query:

• Create embeddings for your data.
• Retrieve LLM chat completions from models like OpenAI GPT4o.
• Reason over your data and facilitate use cases like classification, summarization, and data enrichment on your existing relational data in PostgreSQL.

To learn more, see the pgai documentation.

The 2.15.x releases contains performance improvements and bug fixes. Highlights in these releases are:

• Continuous Aggregate now supports time_bucket with origin and/or offset.
• Hypertable compression has the following improvements:
  • Recommend optimized defaults for segment by and order by when configuring compression through analysis of table configuration and statistics.
  • Added planner support to check more kinds of WHERE conditions before decompression. This reduces the number of rows that have to be decompressed.
  • You can now use minmax sparse indexes when you compress columns with btree indexes.
  • Vectorize filters in the WHERE clause that contain text equality operators and LIKE expressions.

To learn more, see the TimescaleDB release notes.

The PostgreSQL Audit extension(pgaudit) is now available on Timescale Cloud. pgaudit provides detailed database session and object audit logging in the Timescale Cloud logs.

If you have strict security and compliance requirements and need to log all operations on the database level, pgaudit can help. You can also export these audit logs to Amazon CloudWatch.

To learn more, see the pgaudit documentation.

The SI Units for PostgreSQL extension(unit) provides support for the ISU in Timescale Cloud.

You can use Timescale Cloud to solve day-to-day questions. For example, to see what 50°C is in °F, run the following query in your Timescale Cloud service:

SELECT '50°C'::unit @ '°F' as temp;
  temp
--------
 122 °F
(1 row)

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To learn more, see the postgresql-unit documentation.