Timeplus
KSQL
Kafka Streams
Apache Flink
Azure Stream Analytics
Apache NiFi
Azure Data Factory
Apache Airflow
Materialize
Apache Flink
OctoSQL
Apache Kafka
ClickHouse
AwesomeBump
Amazon Kinesis
Slicing Pie
Ready to turn your real-time data into actions?
Timeplus Cloud: Real-Time Analytics Platform is a high-performance converged platform that unifies streaming and historical data processing.
It empowers developers to build powerful and reliable streaming analytics applications, at speed and scale, anywhere.
Timeplus MaterializeNo features have been listed yet.
Based on our record, Materialize seems to be a lot more popular than Timeplus. While we know about 65 links to Materialize, we've tracked only 1 mention of Timeplus. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
* Proton is more developer friendly To explore Proton yourself, visit the [Proton GitHub repo](https://github.com/timeplus-io/proton). - Source: Hacker News / 3 months ago
To fully leverage the data is the new oil concept, companies require a special database designed to manage vast amounts of data instantly. This need has led to different database forms, including NoSQL databases, vector databases, time-series databases, graph databases, in-memory databases, and in-memory data grids. Recent years have seen the rise of cloud-based streaming databases such as RisingWave, Materialize,... - Source: dev.to / 3 months ago
Some recent solutions to this problem include Differential Dataflow and Materialize. It would be neat if postgres adopted something similar for live-updating materialized views. https://github.com/timelydataflow/differential-dataflow. - Source: Hacker News / 7 months ago
Materialize | Full-Time | NYC Office or Remote | https://materialize.com Materialize is an Operational Data Warehouse: A cloud data warehouse with streaming internals, built for work that needs action on what’s happening right now. Keep the familiar SQL, keep the proven architecture of cloud warehouses but swap the decades-old batch computation model for an efficient incremental engine to get complex queries that... - Source: Hacker News / 7 months ago
Materialize | EM (Compute), Senior PM | New York, New York | https://materialize.com/ You shouldn't have to throw away the database to build with fast-changing data. Keep the familiar SQL, keep the proven architecture of cloud warehouses, but swap the decades-old batch computation model for an efficient incremental engine to get complex queries that are always up-to-date. That is Materialize, the only true SQL... - Source: Hacker News / 11 months ago
Materialize | NY, NY | https://materialize.com/ The Cloud Database for Fast-Changing Data. We put a streaming engine in a database, so your team can build real-time data products without the cost, complexity, and development time of stream processing. Cloud team openings: https://grnh.se/0ad6ab6b4us Senior PM openings: https://grnh.se/415c267f4us. - Source: Hacker News / about 1 year ago
KSQL - Confluent KSQL is the streaming SQL engine that enables real-time data processing against Apache Kafka®.
Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
Kafka Streams - Apache Kafka: A Distributed Streaming Platform.
OctoSQL - OctoSQL is a query tool that allows you to join, analyse and transform data from multiple databases and file formats using SQL. - cube2222/octosql
Apache Kafka - Apache Kafka is an open-source message broker project developed by the Apache Software Foundation written in Scala.
Azure Stream Analytics - Azure Stream Analytics offers real-time stream processing in the cloud.
