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22 Top Cloud Database Vendors

by Salvatore Salamone

Cloud migration continues to be a priority for many industries and businesses. One big driver for public cloud adoption is lower costs, followed by more straightforward utilization. Public cloud providers have been highly competitive with their service offerings while building the infrastructure businesses need to deploy and run their applications. One particularly popular segment of the market is their cloud database offerings.

Essentially, businesses are moving their traditional database management systems to cloud infrastructure or starting from scratch with new cloud-native database systems. The vendors in this market offer a wide range of features and services. Some of the most important ones include:

Alibaba Cloud

Alibaba Cloud offers a full range of cloud products and services for databases, networking, security, analytics, and more. The services include elastic compute, data storage, relational databases, big-data processing, and content delivery networks (CDN). It is the largest cloud computing company in China, and it has been expanding its presence into Europe and the Americas. It offers cloud databases that support OLTP, NoSQL, OLAP, and more.

Amazon Web Services

Amazon Web Services is the elephant in the room. Amazon’s revenues from its cloud services typically have grown in the double-digit range (usually 20 to 35 percent) year-over-year. AWS offers a broad range of compute services. That includes a wide variety of types of fully-managed database services. In total, AWS offers 15+ purpose-built engines to support diverse data models, including relational, key-value, in-memory, graph, time-series database services, and more. Additionally, the company touts its high availability and security. It delivers those by supporting multi-region, multi-primary replication and by providing full data oversight with multiple levels of security.


BigQuery is a fully managed enterprise data warehouse on Google Cloud that helps manage and analyze data with built-in features like machine learning, geospatial analysis, and business intelligence. It offers great flexibility by separating the compute engine that analyzes data from storage. Companies can store and analyze data within BigQuery or use BigQuery to assess data where it lives. Developers and data scientists can use client libraries with familiar programming, including Python, Java, JavaScript, and Go, as well as BigQuery’s REST API and RPC API to transform and manage data. ODBC and JDBC drivers provide interaction with existing applications, including third-party tools and utilities.


Cloudera offers a hybrid data platform with secure data management and portable cloud-native data analytics to transform complex data into useful insights. Its Cloudera Data Platform (CDP) combines the data management, analytics, and transactional and data science services of public and private clouds. It includes CDP Data Hub, CDP DataFlow, CDP Data Engineering, CDP Operational Database, CDP Data Warehouse, and CDP Machine Learning. Its operational database-as-a-service brings ease of use and flexibility to Apache HBase users.

Cockroach Labs

Cockroach Labs offers CockroachDB, a distributed SQL database for cloud applications. It is built on a transactional and key-value store technology. It scales horizontally; survives disk, machine, rack, and even data center failures with minimal latency disruption and no manual intervention; supports strongly-consistent ACID transactions; and provides an SQL API for querying data. CockroachDB is built to automatically replicate, rebalance, and recover with minimal configuration and operational overhead. It is well suited for applications that require reliable, available, and correct data, and millisecond response times, regardless of scale.


Couchbase offers Couchbase Capella (DBaaS), a distributed NoSQL database offered as a fully managed service. Capella is a JSON document and key-value database with SQL access and built-in full-text search, eventing, and analytics. It offers enterprise-class performance using a memory-first, high-performance architecture. Additionally, Capella guarantees the global reliability of data throughout regions and availability zones via native replication across geo-aware clusters.


Databricks is a leading proponent of the lakehouse concept, which combines the capabilities of a data lake and a data warehouse operating on the same data. Specifically, its Databricks Lakehouse Platform combines elements of data lakes and data warehouses to deliver the reliability, strong governance, and performance of data warehouses with the openness, flexibility, and machine learning support of data lakes. The strength of the lakehouse approach is that it simplifies data architecture by eliminating the data silos that traditionally separate analytics, BI, data science, and machine learning.

Related: Top Conferences for Data and AI Professionals Working with the Cloud


DataStax offers a massively scalable, highly available, cloud-native NoSQL database built on Apache Cassandra. It offers different solutions. One, Astra DB, is a multi-cloud Database-as-a-Service that simplifies cloud-native Cassandra application development. DataStax Enterprise is a Scale-out, cloud-native NoSQL database built on Apache Cassandra. And its Luna for Apache Cassandra provides those wanting to use the open-source solution with enterprise-class features and support.


The Google Cloud Platform supports many database platform-as-a-service (dbPaaS) products, from fully managed third-party products to its own products. Those products include Google Cloud SQL, Cloud Spanner, Cloud Bigtable, BigQuery, Dataproc, Cloud Firestore, and Firebase Realtime Database. It offers fully managed MySQL, PostgreSQL, and SQL Server databases. And it simplifies migrations to Cloud SQL from MySQL and PostgreSQL with its Database Migration Service. It complements its cloud database offerings with side-by-side data analytics solutions that allow businesses to derive insights from their cloud data.


IBM offerings center around IBM Cloud Pak for Data, a unified integration layer for containerized DBMS services built on Red Hat OpenShift. Cloud Pak for Data serves as a platform for many other IBM data management offerings, including IBM Db2 on Cloud, IBM Db2 Warehouse on Cloud, IBM Cloud SQL Query, IBM Cloudant, the IBM Cloud Database family, and IBM Event Streams, plus managed services for third-party offerings. In addition to IBM’s DBMS offerings (Db2, Netezza, Cloudant), Cloud Pak for Data also supports third-party offerings like DataStax, MongoDB, Redis, and others.


InterSystems offers InterSystems IRIS, a platform for rapidly developing and deploying data-intensive applications. At the heart of the offering is an ultra-high-performance, multi-model, transactional-analytical database engine. With InterSystems IRIS, data is stored once and can be accessed as tables, objects, documents, key-value, or multidimensional arrays. The solution also features a built-in analytics platform to respond to data in real-time, natural language processing tools to analyze unstructured data, integration and interoperability tools, and automation help for easy deployment.

Continued on CloudDataInsights.com



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