Top 10 Cloud Database Engines
Last updated: February 21, 2018
Cloud Database Engines - database management systems that run on a cloud computing platforms with high load.
Apache Cassandra is an open source distributed database management system designed to handle large amounts of data across many commodity servers, providing high availability with no single point of failure. Cassandra offers robust support for clusters spanning multiple datacenters, with asynchronous masterless replication allowing low latency operations for all clients.
MongoDB is an open-source document database, and the leading NoSQL database. Written in C++, MongoDB features: Document-Oriented Storage, Full Index Support, Replication & High Availability, Auto-Sharding, Querying, Fast In-Place Updates, Map/Reduce and others.
Oracle Database introduces a new multitenant architecture that makes it easy to consolidate many databases quickly and manage them as a cloud service. It also includes in-memory data processing capabilities delivering breakthrough analytical performance. Additional database innovations deliver new levels of efficiency, performance, security, and availability. Oracle Database enables customers to plug into the cloud and power the real-time enterprise.
MySQL is the world's most popular open source database. Whether you are a fast growing web property, technology ISV or large enterprise, MySQL can cost-effectively help you deliver high performance, scalable database applications.
SQL Server enables customers to build mission-critical applications and Big Data solutions using high-performance, in-memory technology across OLTP, data warehousing, business intelligence and analytics workloads without having to buy expensive add-ons or high-end appliances. SQL Server uses a common set of tools to deploy and manage databases both on-premises and in the cloud, which makes it easier for customers to take advantage of the cloud with existing skills.
Redis is an open source, BSD licensed, advanced key-value cache and store. It is often referred to as a data structure server since keys can contain strings, hashes, lists, sets, sorted sets, bitmaps and hyperloglogs.
FoundationDB is multi-model, meaning you can store many types data all in a single database. All data is safely stored, distributed, and replicated in the Key-Value Store component, and new functionality, like our SQL Layer, is layered on top of its simple API.
Google Cloud Bigtable offers you a fast, fully managed, massively scalable NoSQL database service that's ideal for web, mobile, and Internet of Things applications requiring terabytes to petabytes of data. Unlike comparable market offerings, Cloud Bigtable doesn't require you to sacrifice speed, scale, or cost efficiency when your applications grow. Cloud Bigtable has been battle-tested at Google for more than 10 years—it's the database driving major applications such as Google Analytics and Gmail.
DocumentDB is a highly scalable, NoSQL document database service offering rich query and transactional processing over a schema-free JSON data model. The service helps you quickly build, grow, and scale applications that run in the cloud when predictable throughput, low latency, and flexible queries are key.
PostgreSQL is a powerful, open source object-relational database system. It has more than 15 years of active development and a proven architecture that has earned it a strong reputation for reliability, data integrity, and correctness. It runs on all major operating systems
One of the most popular database servers. Made by the original developers of MySQL. Guaranteed to stay open source.
Riak is an open source, distributed database. Riak is is designed to store data and serve requests predictably and quickly, even during peak times. Riak replicates and retrieves data intelligently, making it available for read and write operations even in failure conditions. Riak is fault-tolerant so you can lose access to nodes due to network partition or hardware failure and never lose data.
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PipelineDB is an open-source relational database that runs SQL queries continuously on streams, incrementally storing results in tables.