The fastest SQL pipeline engine in a single C++ binary.
Timeplus Proton is a lightweight SQL engine ideal for building streaming pipelines – open source under Apache 2.0 License.
curl https://install.timeplus.com/oss | sh
WHY TIMEPLUS PROTON?
Fast and High Performance
Timeplus Proton is written in C++, with optimized performance through SIMD. On an Apple MacBookPro with M2 Max, Timeplus Proton can deliver 90 million EPS, 4 millisecond end-to-end latency, and high cardinality aggregation with 1 million unique keys. See Example
Lightweight, Single-Binary
Timeplus Proton is a single binary (<500MB). No JVM, ZooKeeper, or other dependencies. You can also run it with Docker, or on an AWS t2.nano instance (1 vCPU and 0.5 GiB memory).
Native Connectors
Timeplus Proton natively connects with with Apache Kafka, Redpanda, Apache Pulsar, ClickHouse, Splunk, Elastic, MongoDB, S3, Apache Iceberg and more. Query live data in Apache Kafka or other compatible streaming data platforms, with external streams.
Streaming SQL for Everything
Full streaming processing end-to-end: ETL, join and aggregation, Materialized Views, Alerts and Tasks. Plus, native Python/JavaScript UDF/UDAF support.
How is Timeplus Proton different from Clickhouse?
ClickHouse is an extremely performant data warehouse built for fast analytical queries on large amounts of data, with support for ingesting data from streaming sources such as Apache Kafka. But it is itself not a stream processing engine which can transform and join streaming event data based on time-based semantics.
While ClickHouse also has incremental materialized view capabilities, it is limited to creating materialized view off of ingestion of blocks to a single table.
Timeplus Proton takes it further:
Timeplus Proton uses ClickHouse as a table store engine inside of each stream (alongside a Write Ahead Log and other data structures), unifying real-time and historical data.
Additionally, Timeplus Proton can act as an advanced data pre-processor for ClickHouse (and similar systems) where the bulk of the data preparation and batching is done ahead of ingestion.