DBMS > Cassandra vs. Hive vs. PostgreSQL vs. Spark SQL vs. YugabyteDB
System Properties Comparison Cassandra vs. Hive vs. PostgreSQL vs. Spark SQL vs. YugabyteDB
| Editorial information provided by DB-Engines | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Name | Cassandra Xexclude from comparison | Hive Xexclude from comparison | PostgreSQL Xexclude from comparison | Spark SQL Xexclude from comparison | YugabyteDB Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Description | Wide-column store based on ideas of BigTable and DynamoDB  Optimized for write access | data warehouse software for querying and managing large distributed datasets, built on Hadoop | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | Spark SQL is a component on top of 'Spark Core' for structured data processing | High-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Wide column store | Relational DBMS | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | Relational DBMS | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary database models | Vector DBMS starting with release V5 | Document store Graph DBMS with Apache AgeSpatial DBMS Vector DBMS with pgvector extension | Document store Wide column store | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
|
|
|
|
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Website | cassandra.apache.org | hive.apache.org | www.postgresql.org | spark.apache.org/sql | www.yugabyte.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | cassandra.apache.org/doc/latest | cwiki.apache.org/confluence/display/Hive/Home | www.postgresql.org/docs | spark.apache.org/docs/latest/sql-programming-guide.html | docs.yugabyte.com github.com/yugabyte/yugabyte-db | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | Apache Software Foundation Apache top level project, originally developped by Facebook | Apache Software Foundation initially developed by Facebook | PostgreSQL Global Development Group www.postgresql.org/developer | Apache Software Foundation | Yugabyte Inc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2008 | 2012 | 1989 1989: Postgres, 1996: PostgreSQL | 2014 | 2017 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | 4.1.3, July 2023 | 3.1.3, April 2022 | 16.3, May 2024 | 3.5.0 ( 2.13), September 2023 | 2.19, September 2023 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | Open Source Apache version 2 | Open Source Apache Version 2 | Open Source BSD | Open Source Apache 2.0 | Open Source Apache 2.0 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | no | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. | Astra DB: Multi-cloud DBaaS built on Apache Cassandra. |
| YugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Implementation language | Java | Java | C | Scala | C and C++ | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | BSD Linux OS X Windows | All OS with a Java VM | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | Linux OS X Windows | Linux OS X | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | schema-free | yes | yes | yes | depending on used data model | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typing predefined data types such as float or date | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT. | no | yes specific XML-type available, but no XML query functionality. | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | restricted only equality queries, not always the best performing solution | yes | yes | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | SQL-like SELECT, DML and DDL statements (CQL) | SQL-like DML and DDL statements | yes standard with numerous extensions | SQL-like DML and DDL statements | yes, PostgreSQL compatible | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | Proprietary protocol CQL (Cassandra Query Language, an SQL-like language) Thrift | JDBC ODBC Thrift | ADO.NET JDBC native C library ODBC streaming API for large objects | JDBC ODBC | JDBC YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Supported programming languages | C# C++ Clojure Erlang Go Haskell Java JavaScript Node.jsPerl PHP Python Ruby Scala | C++ Java PHP Python | .Net C C++ Delphi Java JDBCJavaScript (Node.js) Perl PHP Python Tcl | Java Python R Scala | C C# C++ Go Java JavaScript (Node.js) PHP Python Ruby Rust Scala | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | no | yes user defined functions and integration of map-reduce | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | no | yes sql, plpgsql, C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | yes | no | yes | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | Sharding no "single point of failure" | Sharding | partitioning by range, list and (since PostgreSQL 11) by hash | yes, utilizing Spark Core | Hash and Range Sharding, row-level geo-partitioning | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Replication methods Methods for redundantly storing data on multiple nodes | selectable replication factor Representation of geographical distribution of servers is possible | selectable replication factor | Source-replica replication other methods possible by using 3rd party extensions | none | Based on Raft distributed consensus protocol, minimum 3 replicas for continuous availability | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| MapReduce Offers an API for user-defined Map/Reduce methods | yes | yes query execution via MapReduce | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Immediate Consistency can be individually decided for each write operation | Eventual Consistency | Immediate Consistency | Strong consistency on writes and tunable consistency on reads | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | no | no | yes | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no Atomicity and isolation are supported for single operations | no | ACID | no | Distributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Durability Support for making data persistent | yes | yes | yes | yes | yes based on RocksDB | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | no | no | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| User concepts Access control | Access rights for users can be defined per object | Access rights for users, groups and roles | fine grained access rights according to SQL-standard | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cassandra | Hive | PostgreSQL | Spark SQL | YugabyteDB | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Specific characteristics | Apache Cassandra is the leading NoSQL, distributed database management system, well... » more | YugabyteDB is an open source distributed SQL database for cloud native transactional... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competitive advantages | No single point of failure ensures 100% availability . Operational simplicity for... » more | PostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS.... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typical application scenarios | Internet of Things (IOT), fraud detection applications, recommendation engines, product... » more | Systems of record and engagement for cloud native applications that require resilience,... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Key customers | Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Market metrics | Cassandra is used by 40% of the Fortune 100. » more | 2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Licensing and pricing models | Apache license Pricing for commercial distributions provided by DataStax and available... » more | Apache 2.0 license for the database » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| News | An Introduction to David Jones-Gilardi, Developer Relations Introducing Tejas Kumar, Developer Relations Engineer Indexing All of Wikipedia on a Laptop An Introduction to Phil Nash, Developer Relations Focus on Creativity, Not Clusters: DataStax Mission Control in Action! | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
We invite representatives of system vendors to contact us for updating and extending the system information, | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Related products and services | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 3rd parties | CData: Connect to Big Data & NoSQL through standard Drivers. » more Cassandra Forward event: Want to level up your Cassandra game? Watch now replays of the March 2023 sessions. » more | CYBERTEC is your professional partner in PostgreSQL topics for over 20 years. As our main aim is to be your single-source all-in-one IT service provider, we offer a wide range of products and services. Visit our website for more details. » more Redgate webinars: A series of key topics for new PostgreSQL users. » more Fujitsu Enterprise Postgres: An Enterprise Grade PostgreSQL with the flexibility of a hybrid cloud solution combined with industry leading security, availability and performance. » more pgDash: In-Depth PostgreSQL Monitoring. » more Aiven for PostgreSQL: Fully managed PostgreSQL for developers with 70+ extensions and flexible orchestration tools. » more Navicat for PostgreSQL is an easy-to-use graphical tool for PostgreSQL database development. » more Timescale: Calling all PostgreSQL users – the 2023 State of PostgreSQL survey is now open! Share your favorite extensions, preferred frameworks, community experiences, and more. Take the survey today! » more Navicat Monitor is a safe, simple and agentless remote server monitoring tool for PostgreSQL and many other database management systems. » more Instaclustr: Fully Hosted & Managed PostgreSQL » more SharePlex is the reliable and affordable data replication solution for PostgreSQL migrations, high availability and more. » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
We invite representatives of vendors of related products to contact us for presenting information about their offerings here. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cassandra | Hive | PostgreSQL | Spark SQL | YugabyteDB | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DB-Engines blog posts | Cassandra keeps climbing the ranks of the DB-Engines Ranking Oracle is the DBMS of the Year Winners, losers and an attractive newcomer in Novembers DB-Engines ranking | Why is Hadoop not listed in the DB-Engines Ranking? | PostgreSQL is the DBMS of the Year 2023 Snowflake is the DBMS of the Year 2022, defending the title from last year Snowflake is the DBMS of the Year 2021 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Recent citations in the news | ScyllaDB 6.0 advances open source database scalability Here's What to Know About Apache Cassandra 5.0 Microsoft extends life support for aging Apache Cassandra 3.11 database How Zalando migrated their shopping carts to Amazon DynamoDB from Apache Cassandra | Amazon Web Services Microsoft Build 2024: Cosmos DB for NoSQL gets vector search provided by Google News | Design a data mesh pattern for Amazon EMR-based data lakes using AWS Lake Formation with Hive metastore ... Apache Software Foundation Announces Apache Hive 4.0 Altiscale Becomes First Hadoop-as-a-Service to Deliver Apache Hive 0.13 18 Top Big Data Tools and Technologies to Know About in 2024 ASF Unveils the Next Evolution of Big Data Processing With the Launch of Hive 4.0 provided by Google News | A New Era AI Databases: PostgreSQL with pgvectorscale Outperforms Pinecone and Cuts Costs by 75% with New Open-Source Extensions PostgreSQL is Now Faster than Pinecone, 75% Cheaper, with New Open Source Extensions Timescale unveils high-performance AI vector database extensions for PostgreSQL PostgreSQL Tutorial: Definition, Commands, & Features How To Schedule PostgreSQL Backups With GitHub Actions provided by Google News | Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services What is Apache Spark? The big data platform that crushed Hadoop Performance Insights from Sigma Rule Detections in Spark Streaming Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024 Simba Technologies(R) Introduces New, Powerful JDBC Driver With SQL Connector for Apache Spark(TM) provided by Google News | Yugabyte Achieves PCI DSS Level 1 Compliance, Validating Secure and Scalable Distributed PostgreSQL for ... YugabyteDB Becomes First Distributed SQL Database Vendor to Complete CIS Benchmark The surprising link between Formula One and enterprise PostgreSQL optimisation Yugabyte Embraces 'No Downtime, No Limits,' as the Theme of the Upcoming Distributed SQL Summit Asia Can Yugabyte Become The Defacto Database For Large-Scale, Cloud Native Applications? provided by Google News | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Share this page
