Apache Flink
Apache Spark
Spring Framework
Spark Mail
Amazon Kinesis
Apache Kafka
Grails
Apache Struts
DataStax
Ataccama
Dell EMC DataIQ
1010Data
Redis
Druva
ArangoDB
Hitachi Vantara
Apache Flink DataStaxBased on our record, Apache Flink seems to be a lot more popular than DataStax. While we know about 46 links to Apache Flink, we've tracked only 2 mentions of DataStax. 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.
When IoTDB was initiated in 2011, almost all influential distributed systems and databases were built in Java or on the JVMโsuch as Hadoop, HBase, Spark (Scala on JVM), Cassandra, Kafka, and Flink. To integrate deeply with the big data ecosystem, choosing Java was a natural decision. - Source: dev.to / 4 months ago
In the meantime, other query engine support is on the roadmap, including Apache Spark, Apache Flink, and others. - Source: dev.to / 12 months ago
Many stream processing systems today still rely on local disks and RocksDB to manage state. This model has been around for a while and works fine in simple, single-tenant setups. Apache Flink, for example, uses RocksDB as its default state backend - state is kept on local disks, and periodic checkpoints are written to external storage for recovery. - Source: dev.to / about 1 year ago
Because the hosted catalog is a standard JDBC catalog, tools like Spark, Trino, and Flink can still access your tables. For example:. - Source: dev.to / about 1 year ago
I wrote a python based aircraft monitor which polls the adsb.fi feed for aircraft transponder messages, and publishes each location update as a new event into an Apache Kafka topic. I used Apache Flink โ and more specially Flink SQL, to transform and analyse my flight data. The TL;DR summary is I can write SQL for my real-time data processing queries โ and get the scalability, fault tolerance, and low latency... - Source: dev.to / about 1 year ago
This is the first part of a multipart post about creating a multi-agent research assistant using Datastax AstraDB and Langflow. - Source: dev.to / over 1 year ago
When it comes to building one's own RAG applications, DataStax's Astra seems to be the preferred database solution for deploying RAG applications, thanks to its robust API and integrations that facilitate the development of high-performance RAG applications. Astra DB's architecture supports the high demands of RAG by providing low latency and high relevancy in data retrieval, which are pretty important for the... - Source: dev.to / about 2 years ago
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
Ataccama - We deliver Self-Driving Data Management & Governance with Ataccama ONE. Itโs a fully integrated yet modular platform for any data, user, domain, or deployment.
Spring Framework - The Spring Framework provides a comprehensive programming and configuration model for modern Java-based enterprise applications - on any kind of deployment platform.
Dell EMC DataIQ - Dell EMC DataIQ is one of the unique storage monitoring and dataset management software for unstructured data that allows a unified file system of PowerScale, ECS, and delivers unique insights into data usage and storage system health.
Spark Mail - Spark helps you take your inbox under control. Instantly see whatโs important and quickly clean up the rest. Spark for Teams allows you to create, discuss, and share email with your colleagues
1010Data - 1010data provides cloud-based big data analytics for retail, manufacturing, telecom and financial services enterprises.
