We are thrilled to introduce our latest update to Timeplus Cloud.
Since our public beta launch in October 2022, we’ve had many conversations with developers and data engineers about streaming processing and analytics (landscape), the challenges they were facing, and how Timeplus was doing to minimize these technical headaches.
We’ve received a lot of positive feedback on our cloud product:
Developers appreciate how the easy set up enables them to scale streaming infrastructure with minimal additional engineering resources. This helps developers deliver value quickly - and at far lower TCO - to their business units.
Data engineers are also leveraging our unified historical + streaming analytics in exciting ways. The unified analytics powers companies to process and monitor streaming data with single-digit millisecond latency, while enabling them to dig into root cause analysis with historical data “time travel”.
Developers also like the ability to use Timeplus to access third-party data systems (via federated queries), thereby simplifying their analytics stack set up.
But we’ve also heard where we could be doing more. Developers told us we could do even more to improve usability. They also asked us to work on better system extensibility: specifically, to provide easier and more performant User-Defined Function (UDF) and User-Defined Aggregation Function(UDAF). They also asked for more options for real-time charts and dashboards to better visualize streaming data.
We’ve listened to your feedback. We are happy to share our biggest product update to date.
Key Highlights
The key enhancements since our December cloud update are:
We are the first few vendors to implement the “SUBSCRIBE TO ..” syntax for streaming query processing which enables reliable query state management, recommended by the INCITS/Data Management Technical Committee. This improves fault tolerance and disaster recovery for your critical analytics workload.
We introduced an experimental framework for JavaScript-based User-Defined Functions (UDF), and a User Defined Aggregation Function (UDAF) preview feature which enables powerful contextual event processing capabilities to cover more use cases like IoT and security.
JSON is a first class built-in data type now. With it, we can support dynamic schema changes, improving storage efficiency, query performance and usability.
We completely support substream over multiple shards now. Data shuffling, reshuffling is automatically done via `partition by`. This capability enables handling larger data volumes in substream scenarios.
There are lots of other improvements like stability, query optimization in JOIN like more aggressive predicates push down, concurrent JOIN, concurrent aggregation etc.
We added the built-in workflow for alerts. You can define when the alerts should be triggered and when they should be cleared with SQL, and easily integrate with systems like Slack or PagerDuty.
The streaming exploration and query result interface are greatly improved. You can apply a quick filter with keywords in the frontend without submitting a new SQL. You can also get the live summary of min/max/avg for numeric columns.
More types of streaming charts are now available. You don’t have to send the analytics result to a database and use another tool to visualize the data.
Check out these screenshots below for a peek at what’s new. We will be hosting another webinar in February to deep-dive into these new features. Stay tuned for details.
Experimental framework for JavaScript-based User-Defined Functions
Updates to the query results table
More chart options
Summary
It’s an exciting time for the streaming ecosystem. Confluent’s recent announcement of its intent to acquire Immerok has brought renewed focus to stream processing, and the critical role it plays in unlocking data value for critical real-time applications. We are thrilled that Timeplus Cloud is helping developers from small to large companies alike derive value from their streaming data with minimal hassle. We look forward to hearing your feedback on our latest features, we think you’ll love them!