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DBMS > CrateDB vs. Heroic vs. SingleStore vs. Trafodion

System Properties Comparison CrateDB vs. Heroic vs. SingleStore vs. Trafodion

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonHeroic  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionDistributed Database based on LuceneTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchMySQL 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 typeTransactional SQL-on-Hadoop DBMS
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Time Series DBMSRelational DBMSRelational DBMS
Secondary database modelsRelational DBMSDocument store
Spatial DBMS
Time Series DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.69
Rank#226  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#11  Vector DBMS
Score0.13
Rank#335  Overall
#29  Time Series DBMS
Score4.02
Rank#74  Overall
#39  Relational DBMS
Websitecratedb.comgithub.com/­spotify/­heroicwww.singlestore.comtrafodion.apache.org
Technical documentationcratedb.com/­docsspotify.github.io/­heroicdocs.singlestore.comtrafodion.apache.org/­documentation.html
DeveloperCrateSpotifySingleStore Inc.Apache Software Foundation, originally developed by HP
Initial release2013201420132014
Current release5.8.1, August 20248.5, January 20242.3.0, February 2019
License infoCommercial or Open SourceOpen SourceOpen Source infoApache 2.0commercial infofree developer edition availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC++, GoC++, Java
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinux info64 bit version requiredLinux
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nononono
Secondary indexesyesyes infovia Elasticsearchyesyes
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilitynoyes infobut no triggers and foreign keysyes
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Cluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
ADO.NET
JDBC
ODBC
Supported programming languages.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
Bash
C
C#
Java
JavaScript (Node.js)
Python
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresuser defined functions (Javascript)noyesJava Stored Procedures
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infohash partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelyesSource-replica replication infostores two copies of each physical data partition on two separate nodesyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono infocan define user-defined aggregate functions for map-reduce-style calculationsyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Eventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infounique row identifiers can be used for implementing an optimistic concurrency control strategynoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlrights management via user accountsFine grained access control via users, groups and rolesfine grained access rights according to SQL-standard

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More resources
CrateDBHeroicSingleStore infoformer name was MemSQLTrafodion
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Recent citations in the news

CrateDB Appoints Jeff Olson as New CRO
9 July 2024, PR Newswire

CrateDB Announces Availability of CrateDB on Google Cloud Marketplace
8 April 2024, Datanami

Taleo Consulting and CrateDB Announce Strategic Partnership to Transform Data Management and Analytics in Financial Services markets
29 July 2024, PR Newswire

How We Designed CrateDB as a Realtime SQL DBMS for the Internet of Things
29 August 2017, The New Stack

CrateDB Appoints Sergey Gerasimenko as New CTO
19 February 2024, PR Newswire

provided by Google News

SingleStore Partners With Snowflake to Help Users Build Faster, More Efficient Real Time AI Applications
19 September 2024, Business Wire

Third time was the charm for SingleStore in the cloud, CEO says
8 July 2024, The Register

SingleStore CEO sees little future for purpose-built vector databases
24 January 2024, VentureBeat

Achieve near real-time analytics on Amazon DynamoDB with SingleStore
16 September 2024, AWS Blog

Building a Modern Database: Nikita Shamgunov on Postgres and Beyond
18 April 2024, Madrona Venture Group

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