DBMS > Cassandra vs. Couchbase vs. Heroic vs. InfluxDB vs. SingleStore
System Properties Comparison Cassandra vs. Couchbase vs. Heroic vs. InfluxDB vs. SingleStore
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Name | Cassandra Xexclude from comparison | Couchbase Originally called Membase Xexclude from comparison | Heroic Xexclude from comparison | InfluxDB Xexclude from comparison | SingleStore former name was MemSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Wide-column store based on ideas of BigTable and DynamoDB Optimized for write access | A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database | Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch | DBMS for storing time series, events and metrics | MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Wide column store | Document store | Time Series DBMS | Time Series DBMS | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Vector DBMS starting with release V5 | Key-value store originating from the former Membase product and supporting the Memcached protocol Spatial DBMS using the Geocouch extension Search engine Time Series DBMS Vector DBMS | Spatial DBMS with GEO package | Document store Spatial DBMS Time Series DBMS Vector DBMS | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | cassandra.apache.org | www.couchbase.com | github.com/spotify/heroic | www.influxdata.com/products/influxdb-overview | www.singlestore.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | cassandra.apache.org/doc/latest | docs.couchbase.com | spotify.github.io/heroic | docs.influxdata.com/influxdb | docs.singlestore.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Apache Software Foundation Apache top level project, originally developped by Facebook | Couchbase, Inc. | Spotify | SingleStore Inc. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2008 | 2011 | 2014 | 2013 | 2013 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 4.1.3, July 2023 | Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023 | 2.7.6, April 2024 | 8.5, January 2024 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source Apache version 2 | Open Source Business Source License (BSL 1.1); Commercial licenses also available | Open Source Apache 2.0 | Open Source MIT-License; commercial enterprise version available | commercial free developer edition available | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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. | SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | Java | C, C++, Go and Erlang | Java | Go | C++, Go | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | BSD Linux OS X Windows | Linux OS X Windows | Linux OS X through Homebrew | Linux 64 bit version required | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free | schema-free | schema-free | schema-free | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes | yes | Numeric data and Strings | 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 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | restricted only equality queries, not always the best performing solution | yes | yes via Elasticsearch | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | SQL-like SELECT, DML and DDL statements (CQL) | SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases | no | SQL-like query language | yes but no triggers and foreign keys | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | Proprietary protocol CQL (Cassandra Query Language, an SQL-like language) Thrift | CLI Client HTTP REST Kafka Connector Native language bindings for CRUD, Query, Search and Analytics APIs Spark Connector Spring Data | HQL (Heroic Query Language, a JSON-based language) HTTP API | HTTP API JSON over UDP | Cluster Management API as HTTP Rest and CLI HTTP API JDBC MongoDB API ODBC | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | C# C++ Clojure Erlang Go Haskell Java JavaScript Node.js Perl PHP Python Ruby Scala | .Net C Go Java JavaScript Node.js Kotlin PHP Python Ruby Scala | .Net Clojure Erlang Go Haskell Java JavaScript JavaScript (Node.js) Lisp Perl PHP Python R Ruby Rust Scala | Bash C C# Java JavaScript (Node.js) Python | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | no | Functions and timers in JavaScript and UDFs in Java, Python, SQL++ | no | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes | yes via the TAP protocol | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding no "single point of failure" | Automatic Sharding | Sharding | Sharding in enterprise version only | Sharding hash partitioning | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | selectable replication factor Representation of geographical distribution of servers is possible | Multi-source replication including cross data center replication Source-replica replication | yes | selectable replication factor in enterprise version only | Source-replica replication stores two copies of each physical data partition on two separate nodes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | yes | yes | no | no | no can define user-defined aggregate functions for map-reduce-style calculations | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 selectable on a per-operation basis | Eventual Consistency Immediate Consistency | Immediate Consistency | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no Atomicity and isolation are supported for single operations | ACID | no | no | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes, multi-version concurrency control (MVCC) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes | yes | yes All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | no | yes Ephemeral buckets | no | yes Depending on used storage engine | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Access rights for users can be defined per object | User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control. | simple rights management via user accounts | Fine grained access control via users, groups and roles | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cassandra | Couchbase Originally called Membase | Heroic | InfluxDB | SingleStore former name was MemSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | SingleStore offers a fully-managed , distributed, highly-scalable SQL database designed... » 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 | SingleStore’s competitive advantages include: Easy and Simplified Architecture with... » 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 | Driving Fast Analytics: SingleStore delivers the fastest and most scalable reporting... » 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 | IEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,... » 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 | Customers in various industries worldwide including US and International Industry... » 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 | F ree Tier and Enterprise Edition » 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 | Efficiency Unleashed: Streamlining Workflows with the InfluxDB Management API What is DevRel at InfluxData An Introductory Guide to Grafana Alerts What to Expect When You’re Expecting InfluxDB: A Guide Introduction to Apache Iceberg | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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3rd parties | Cassandra Forward event: Want to level up your Cassandra game? Watch now replays of the March 2023 sessions. » more CData: Connect to Big Data & NoSQL through standard Drivers. » more | CData: Connect to Big Data & NoSQL through standard Drivers. » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cassandra | Couchbase Originally called Membase | Heroic | InfluxDB | SingleStore former name was MemSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | Couchbase climbs up the DB-Engines Ranking, increasing its popularity by 10% every month | 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? | Turbocharge Your Application Development Using WebAssembly With SingleStoreDB Cloud-Based Analytics With SingleStoreDB SingleStore: The Increasing Momentum of Multi-Model Database Systems Microsoft Build 2024: Cosmos DB for NoSQL gets vector search Why Apache Cassandra 5.0 Is a Game-Changer for Developers Cassandra is the “best f*cking database for gen AI,” says DataStax CEO How Uber Optimized Cassandra Operations At Scale Here's What to Know About Apache Cassandra 5.0 provided by Google News Couchbase (NASDAQ:BASE) Receives New Coverage from Analysts at UBS Group 11 Analysts Have This To Say About Couchbase UBS Starts Couchbase Inc (BASE) at Neutral Couchbase executive Margaret Chow sells over $137k in stock Couchbase Announces New Features to Accelerate AI-Powered Adaptive Applications for Customers provided by Google News Review: Google Bigtable scales with ease provided by Google News Introducing Amazon Timestream for InfluxDB: A managed service for the popular open source time-series database ... 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 Run and manage open source InfluxDB databases with Amazon Timestream | Amazon Web Services provided by Google News SingleStore CEO sees little future for purpose-built vector databases SingleStore Announces Real-time Data Platform to Further Accelerate AI, Analytics and Application Development Building a Modern Database: Nikita Shamgunov on Postgres and Beyond SingleStore adds indexed vector search to Pro Max release for faster AI work – Blocks and Files SingleStore, Snowflake Help Customers Build Enterprise-Ready Generative AI Apps provided by Google News |
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