risingwave
ksql
| risingwave | ksql | |
|---|---|---|
| 27 | 4 | |
| 6,309 | 5,817 | |
| 2.2% | 0.4% | |
| 10.0 | 10.0 | |
| 5 days ago | 6 days ago | |
| Rust | Java | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
risingwave
-
Proton, a fast and lightweight alternative to Apache Flink
How does this compare to RisingWave and Materialize?
https://github.com/risingwavelabs/risingwave
-
RisingWave's Roadmap - Redefining Stream Processing with the Rust-Built Streaming Database
Hey everyone - One and a half year ago, we open sourced RisingWave, a Rust-built streaming database, under Apache 2.0 license. Two weeks ago, we released RisingWave 1.3. Just last week, we unveiled RisingWave's roadmap.
- Risingwave: Redefining Stream Processing
-
Highlights of RisingWave v1.3: The Open-Source Streaming Database
Look out for next month’s edition to see what new, exciting features will be added. Check out the RisingWave GitHub repository to stay up to date on the newest features and planned releases.
- Optimizing Rust Code for the Lsm-Tree Iterator in RisingWave
- Hummock: A Storage Engine Designed for Stream Processing
-
RisingWave 1.2 released - the open-source streaming database built in Rust
If interested, please feel free to join our Slack community! Thanks eveyone for your generous support!
-
Query materialized views with Java, Spring, and streaming database
We will spin up on our local environment the existing RisingWave fully-featured demo cluster on GitHub which is composed of multiple RisingWave components. To simplify this task, it leverages docker-compose.yaml file which includes additional containers for Kafka message broker, and data generation service.
-
Real-time Data Processing Pipeline With MongoDB, Kafka, Debezium And RisingWave
To complete the steps in this guide, you must download/clone and work on an existing sample project on GitHub. The project uses Docker for convenience and consistency. It provides a containerized development environment that includes the services you need to build the sample data pipeline.
-
Flink CDC / alternatives
Hey have you looked at RisingWave (https://github.com/risingwavelabs/risingwave) before? It's a stream processing system with PostgreSQL interface. It also have integrations similar to Flink CDC.
ksql
- Supercharge your Kafka Clusters with Consumer Best Practices
- The Next Generation of Materialize
- PranaDB
-
Stream processing with sql and a nice gui? Alternatives to lenses.io?
Yeah, it’s community license — https://github.com/confluentinc/ksql/blob/master/LICENSE-ConfluentCommunity
What are some alternatives?
materialize - The data warehouse for operational workloads.
kafka-connect-elasticsearch - Kafka Connect Elasticsearch connector
datafuse - An elastic and reliable Cloud Warehouse, offers Blazing Fast Query and combines Elasticity, Simplicity, Low cost of the Cloud, built to make the Data Cloud easy [Moved to: https://github.com/datafuselabs/databend]
kpow-streams-agent - Monitor Kafka Streams applications with Kpow
greptimedb - An open-source, cloud-native, distributed time-series database with PromQL/SQL/Python supported. Available on GreptimeCloud.
pranadb
chdb - chDB is an embedded OLAP SQL Engine 🚀 powered by ClickHouse
kafka-connect-file-pulse - 🔗 A multipurpose Kafka Connect connector that makes it easy to parse, transform and stream any file, in any format, into Apache Kafka
roapi - Create full-fledged APIs for slowly moving datasets without writing a single line of code.
debezium - Change data capture for a variety of databases. Please log issues at https://issues.redhat.com/browse/DBZ.
arroyo - Distributed stream processing engine in Rust
cruise-control - Cruise-control is the first of its kind to fully automate the dynamic workload rebalance and self-healing of a Kafka cluster. It provides great value to Kafka users by simplifying the operation of Kafka clusters.