SEPT 17-18, AUSTIN, TX
BOOTH #404
Thanks for coming by our booth!
Enter our giveaway for your chance to win a pair of Ray-Ban Meta Smart Glasses. We will draw the lucky winner on Wednesday, at 4:45pm.
Timeplus simplifies stateful stream processing and analytics with a fast, single-binary engine.
By using SQL to define stream processing pipelines and combining row and column-based state stores, we enable developers to build real-time applications, data pipelines, and dashboards at the edge or cloud, reducing the time, complexity, and cost of traditional multi-component stacks.
Why Timeplus?
Unified Streaming and Historical Data Processing
High performance with internal Write Ahead Log (WAL) and Historical Store.
Append-Only and Mutable Streams
Mutable streams support UPSERTs and DELETEs, using a row-based store.
Multi-JOINs and
ASOF JOINs
Join multiple streams, correlate historical trends using ASOF Joins.
External Stream and
External Table
Apache Kafka, Confluent Cloud, Apache Pulsar, ClickHouse, and more
A Lightweight, Single Binary
Runs in bare-metal or Kubernetes environments, from edge to cloud, using a single binary.
Python and JavaScript
User Defined Functions
Extend Timeplus to encapsulate custom logic for both stateless and stateful queries.
Collection
Built-in external streams and external tables to natively collect real-time data from, or send data to: Apache Kafka, Confluent Cloud, Redpanda, ClickHouse, another Timeplus instance, and more.
Transformation
With a powerful streaming SQL console, create Streams, Views, and incremental Materialized Views, to transform, roll up, join, correlate, enrich, aggregate, and downsample real-time data.
Routing
Data can be routed to different sinks based on SQL-based criteria. See a data lineage of all derived streams in the Timeplus web console.
Analytics and Alerting
Powered by SSE (Server-Sent Events), Timeplus supports push-based, low-latency dashboards.
SQL-based rules can be used to trigger or resolve alerts in downstream platforms.
From Kafka to action in no time.
Timeplus simplifies stateful stream processing and analytics with a fast, single-binary engine.
By using SQL to define stream processing pipelines and combining row and column-based state stores, we enable developers to build real-time applications, data pipelines, and dashboards at the edge or cloud, reducing the time, complexity, and cost of traditional multi-component stacks.