DBMS > Cassandra vs. HEAVY.AI vs. InfluxDB vs. Kinetica vs. PostgreSQL
System Properties Comparison Cassandra vs. HEAVY.AI vs. InfluxDB vs. Kinetica vs. PostgreSQL
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Name | Cassandra Xexclude from comparison | HEAVY.AI Formerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022 Xexclude from comparison | InfluxDB Xexclude from comparison | Kinetica Xexclude from comparison | PostgreSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Wide-column store based on ideas of BigTable and DynamoDB Optimized for write access | A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware | DBMS for storing time series, events and metrics | Fully vectorized database across both GPUs and CPUs | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Wide column store | Relational DBMS | Time Series DBMS | Relational DBMS | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Vector DBMS starting with release V5 | Spatial DBMS | Spatial DBMS with GEO package | Spatial DBMS Time Series DBMS | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | cassandra.apache.org | github.com/heavyai/heavydb www.heavy.ai | www.influxdata.com/products/influxdb-overview | www.kinetica.com | www.postgresql.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | cassandra.apache.org/doc/latest | docs.heavy.ai | docs.influxdata.com/influxdb | docs.kinetica.com | www.postgresql.org/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Apache Software Foundation Apache top level project, originally developped by Facebook | HEAVY.AI, Inc. | Kinetica | PostgreSQL Global Development Group www.postgresql.org/developer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2008 | 2016 | 2013 | 2012 | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 4.1.3, July 2023 | 5.10, January 2022 | 2.7.6, April 2024 | 7.1, August 2021 | 16.3, May 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source Apache version 2 | Open Source Apache Version 2; enterprise edition available | Open Source MIT-License; commercial enterprise version available | commercial | Open Source BSD | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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. |
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Implementation language | Java | C++ and CUDA | Go | C, C++ | C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | BSD Linux OS X Windows | Linux | Linux OS X through Homebrew | Linux | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free | yes | schema-free | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes | Numeric data and Strings | 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 | no | no | no | yes specific XML-type available, but no XML query functionality. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | restricted only equality queries, not always the best performing solution | no | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | SQL-like SELECT, DML and DDL statements (CQL) | yes | SQL-like query language | SQL-like DML and DDL statements | yes standard with numerous extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | Proprietary protocol CQL (Cassandra Query Language, an SQL-like language) Thrift | JDBC ODBC Thrift Vega | HTTP API JSON over UDP | JDBC ODBC RESTful HTTP API | ADO.NET JDBC native C library ODBC streaming API for large objects | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | C# C++ Clojure Erlang Go Haskell Java JavaScript Node.js Perl PHP Python Ruby Scala | All languages supporting JDBC/ODBC/Thrift Python | .Net Clojure Erlang Go Haskell Java JavaScript JavaScript (Node.js) Lisp Perl PHP Python R Ruby Rust Scala | C++ Java JavaScript (Node.js) Python | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | no | no | no | user defined functions | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes | no | no | yes triggers when inserted values for one or more columns fall within a specified range | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding no "single point of failure" | Sharding Round robin | Sharding in enterprise version only | Sharding | partitioning by range, list and (since PostgreSQL 11) by hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | selectable replication factor Representation of geographical distribution of servers is possible | Multi-source replication | selectable replication factor in enterprise version only | Source-replica replication | Source-replica replication other methods possible by using 3rd party extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | yes | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Immediate Consistency can be individually decided for each write operation | Immediate Consistency | Immediate Consistency or Eventual Consistency depending on configuration | Immediate Consistency | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | no | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no Atomicity and isolation are supported for single operations | no | no | no | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | no | yes | yes Depending on used storage engine | yes GPU vRAM or System RAM | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Access rights for users can be defined per object | fine grained access rights according to SQL-standard | simple rights management via user accounts | Access rights for users and roles on table level | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cassandra | HEAVY.AI Formerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022 | InfluxDB | Kinetica | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | Apache Cassandra is the leading NoSQL, distributed database management system, well... » more | InfluxData is the creator of InfluxDB , the open source time series database. It... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | No single point of failure ensures 100% availability . Operational simplicity for... » more | Time to Value InfluxDB is available in all the popular languages and frameworks,... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | Internet of Things (IOT), fraud detection applications, recommendation engines, product... » more | IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best... » more | InfluxData has more than 1,900 paying customers, including customers include MuleSoft,... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | Cassandra is used by 40% of the Fortune 100. » more | Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | Apache license Pricing for commercial distributions provided by DataStax and available... » more | Open source core with closed source clustering available either on-premise or on... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
News | How Concide Built its Chat Platform with Enhanced Document Management for Legal Tech Professionals Astra Vectorize: Generate Vector Embeddings with 1 Line of Code GitHub Copilot + DataStax Astra DB: Build GenAI Apps 100x Faster | Webinar Recap: Unleash the Full Potential of Your Time Series Data with InfluxDB and AWS Using Parquet’s Bloom Filters Efficiency Unleashed: Streamlining Workflows with the InfluxDB Management API What is DevRel at InfluxData An Introductory Guide to Grafana Alerts | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Cassandra | HEAVY.AI Formerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022 | InfluxDB | Kinetica | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 Build a Time Series Data Platform? Time Series DBMS are the database category with the fastest increase in popularity Time Series DBMS as a new trend? | 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 Cassandra is the “best f*cking database for gen AI,” says DataStax CEO Here's What to Know About Apache Cassandra 5.0 Why Apache Cassandra 5.0 Is a Game-Changer for Developers How Uber Optimized Cassandra Operations At Scale Microsoft extends life support for aging Apache Cassandra 3.11 database provided by Google News Big Data Analytics: A Game Changer for Infrastructure HEAVY.AI Launches HEAVY 7.0, Introducing Real-Time Machine Learning Capabilities OmniSci Gets HEAVY New Name and New CEO Making the most of geospatial intelligence The insideBIGDATA IMPACT 50 List for Q4 2023 provided by Google News Run and manage open source InfluxDB databases with Amazon Timestream | Amazon Web Services Amazon Timestream: Managed InfluxDB for Time Series Data InfluxData Collaborating with AWS to Bring InfluxDB and Time Series Analytics to Developers Around the World How the FDAP Stack Gives InfluxDB 3.0 Real-Time Speed, Efficiency AWS and InfluxData partner to offer managed time series database Timestream for InfluxDB provided by Google News Kinetica Delivers Real-Time Vector Similarity Search Kinetica Elevates RAG with Fast Access to Real-Time Data Kinetica ramps up RAG for generative AI, empowering enterprises with real-time operational data Kinetica Launches Generative AI Solution for Real-Time Inferencing Powered by NVIDIA AI Enterprise Transforming spatiotemporal data analysis with GPUs and generative AI provided by Google News How to implement a better like, views, comment counters in PostgreSQL? PostgreSQL 17: Part 4 or Commitfest 2024-01 How LeadSquared accelerated chatbot deployments with generative AI using Amazon Bedrock and Amazon Aurora ... Introducing OCI Database with PostgreSQL: Completing Our Cloud Database Suite for Every Need EDB unveils EDB Postgres AI provided by Google News |
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