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DBMS > CrateDB vs. EsgynDB vs. GridDB vs. TimescaleDB

System Properties Comparison CrateDB vs. EsgynDB vs. GridDB vs. TimescaleDB

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonEsgynDB  Xexclude from comparisonGridDB  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionDistributed Database based on LuceneEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionScalable in-memory time series database optimized for IoT and Big DataA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSTime Series DBMSTime Series DBMS
Secondary database modelsRelational DBMSKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.76
Rank#226  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#18  Time Series DBMS
#8  Vector DBMS
Score0.26
Rank#311  Overall
#141  Relational DBMS
Score2.00
Rank#137  Overall
#11  Time Series DBMS
Score5.33
Rank#72  Overall
#4  Time Series DBMS
Websitecratedb.comwww.esgyn.cngriddb.netwww.timescale.com
Technical documentationcratedb.com/­docsdocs.griddb.netdocs.timescale.com
DeveloperCrateEsgynToshiba CorporationTimescale
Initial release2013201520132017
Current release5.1, August 20222.13.0, November 2023
License infoCommercial or Open SourceOpen SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also 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.
CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.
Implementation languageJavaC++, JavaC++C
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinuxLinuxLinux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesyes
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nononoyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilityyesSQL92, SQL-like TQL (Toshiba Query Language)yes infofull PostgreSQL SQL syntax
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
ADO.NET
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
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
All languages supporting JDBC/ODBC/ADO.NetC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functions (Javascript)Java Stored Proceduresnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelMulti-source replication between multi datacentersSource-replica replicationSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Immediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
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 strategyACIDACID at container levelACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
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 rights according to SQL-standardAccess rights for users can be defined per databasefine grained access rights according to SQL-standard
More information provided by the system vendor
CrateDBEsgynDBGridDBTimescaleDB
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
GitHub trending repository
» more
Licensing and pricing modelsSee CrateDB pricing >
» more
Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
CrateDBEsgynDBGridDBTimescaleDB
Recent citations in the news

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

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

Real-Time Analytics Database Company CrateDB Names Lars Färnström as New CEO
1 March 2023, Business Wire

CrateDB 4.5 takes distributed SQL database open source
24 March 2021, TechTarget

Crate.io raises $10M to grow its database platform
15 June 2021, VentureBeat

provided by Google News

General Availability of GridDB 5.3 Enterprise Edition ~ Major Enhancement in IoT and Time Series Data Analysis ...
16 May 2023, global.toshiba

Toshiba launches cloudy managed IoT database service running its own GridDB
8 April 2021, The Register

Toshiba's Distributed Database GridDB(R) Now Features Scale-Out and Scale-Up combo for Petabyte-scale Data ...
3 December 2019, global.toshiba

General Availability of GridDB 5.1 Enterprise Edition ~ Continuous database usage in the event of data center failure ...
19 August 2022, global.toshiba

Leveraging Open Source Tools for IoT - open source for you
19 February 2020, Open Source For You

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TimescaleDB Is a Vector Database Now, Too
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Timescale Introduces Dynamic PostgreSQL, an Alternative to Serverless Databases
19 November 2023, InfoQ.com

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Power IoT and time-series workloads with TimescaleDB for Azure Database for PostgreSQL
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