ArangoDB
Redis
MongoDB
OrientDB
neo4j
Apache Cassandra
Azure Cosmos DB
CouchBase
Apache Beam
Google Cloud Dataflow
Google BigQuery
Snowflake
Qubole
Amazon EMR
Apache Spark
Databricks
ArangoDB Apache BeamBased on our record, Apache Beam should be more popular than ArangoDB. It has been mentiond 15 times since March 2021. 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.
If you like the document db idea there are a lot of choices, especially https://arangodb.com/ which I think gets little attention because people who use it see it as a secret weapon. Too bad about the license though. Also https://couchdb.apache.org/ and https://developer.marklogic.com/. - Source: Hacker News / 9 months ago
ArangoDB is a multi-model database that supports document, key-value, and graph data models with a unified query language. - Source: dev.to / 11 months ago
In modern databases, efficient data serialization and deserialization are paramount to achieving high performance. ArangoDB, a multi-model database, addresses this need with its innovative binary data format, VelocyPack. This article delves into the intricacies of VelocyPack, demonstrating its advantages, usage, and how it enhances the performance of ArangoDB with code examples in Java and Rust. - Source: dev.to / 12 months ago
ArangoDB: A native multi-model database, it offers flexibility for documents, graphs, and key-values. This versatility makes it suitable for applications requiring a combination of these data models. - Source: dev.to / about 1 year ago
ArangoDB, a "multi-modal" database engine that stores arbitrary JSON documents like MongoDB, key/value data like Redis, and graph relationships like Neo4j — and lets you leverage all three kinds of data in a single query. Source: over 2 years ago
Use distributed data processing frameworks like Apache Beam or Apache Spark. - Source: dev.to / 12 days ago
The "streaming systems" book answers your question and more: https://www.oreilly.com/library/view/streaming-systems/9781491983867/. It gives you a history of how batch processing started with MapReduce, and how attempts at scaling by moving towards streaming systems gave us all the subsequent frameworks (Spark, Beam, etc.). As for the framework called MapReduce, it isn't used much, but its descendant... - Source: Hacker News / over 1 year ago
Apache Beam is one of many tools that you can use. Source: over 1 year ago
Apache Beam: Streaming framework which can be run on several runner such as Apache Flink and GCP Dataflow. - Source: dev.to / over 2 years ago
Apache Beam: Batch/streaming data processing 🔗Link. - Source: dev.to / over 2 years ago
Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.
Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.
MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
OrientDB - OrientDB - The World's First Distributed Multi-Model NoSQL Database with a Graph Database Engine.
Snowflake - Snowflake is the only data platform built for the cloud for all your data & all your users. Learn more about our purpose-built SQL cloud data warehouse.