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DBMS > CrateDB vs. IRONdb vs. JaguarDB vs. Transwarp StellarDB

System Properties Comparison CrateDB vs. IRONdb vs. JaguarDB vs. Transwarp StellarDB

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonIRONdb  Xexclude from comparisonJaguarDB  Xexclude from comparisonTranswarp StellarDB  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionDistributed Database based on LuceneA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityPerformant, highly scalable DBMS for AI and IoT applicationsA distributed graph DBMS built for enterprise-level graph applications
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Time Series DBMSKey-value store
Vector DBMS
Graph DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
#13  Vector DBMS
Score0.00
Rank#383  Overall
#39  Graph DBMS
Websitecratedb.comwww.circonus.com/solutions/time-series-database/www.jaguardb.comwww.transwarp.cn/­en/­product/­stellardb
Technical documentationcratedb.com/­docsdocs.circonus.com/irondb/category/getting-startedwww.jaguardb.com/­support.html
DeveloperCrateCirconus LLC.DataJaguar, Inc.Transwarp
Initial release201320172015
Current releaseV0.10.20, January 20183.3 July 2023
License infoCommercial or Open SourceOpen SourcecommercialOpen Source infoGPL V3.0commercial
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 and C++C++ infothe server part. Clients available in other languages
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinuxLinux
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsyes
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.nonono
Secondary indexesyesnoyes
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilitySQL-like query language (Circonus Analytics Query Language: CAQL)A subset of ANSI SQL is implemented infobut no views, foreign keys, triggersSQL-like query language
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
HTTP APIJDBC
ODBC
OpenCypher
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
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresuser defined functions (Javascript)yes, in Luano
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodeShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelconfigurable replication factor, datacenter awareMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Immediate consistency per node, eventual consistency across nodesEventual Consistency
Foreign keys infoReferential integritynonono
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 strategynono
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.nonono
User concepts infoAccess controlrights management via user accountsnorights management via user accountsyes
More information provided by the system vendor
CrateDBIRONdbJaguarDBTranswarp StellarDB
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more

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CrateDBIRONdbJaguarDBTranswarp StellarDB
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