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DBMS > Apache Doris vs. Apache IoTDB vs. CrateDB vs. jBASE

System Properties Comparison Apache Doris vs. Apache IoTDB vs. CrateDB vs. jBASE

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Editorial information provided by DB-Engines
NameApache Doris  Xexclude from comparisonApache IoTDB  Xexclude from comparisonCrateDB  Xexclude from comparisonjBASE  Xexclude from comparison
DescriptionAn MPP-based analytics DBMS embracing the MySQL protocolAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkDistributed Database based on LuceneA robust multi-value DBMS comprising development tools and middleware
Primary database modelRelational DBMSTime Series DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Multivalue DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.61
Rank#235  Overall
#110  Relational DBMS
Score1.31
Rank#159  Overall
#14  Time Series DBMS
Score0.69
Rank#226  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#11  Vector DBMS
Score1.36
Rank#157  Overall
#3  Multivalue DBMS
Websitedoris.apache.org
github.com/­apache/­doris
iotdb.apache.orgcratedb.comwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-jbase
Technical documentationgithub.com/­apache/­doris/­wikiiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlcratedb.com/­docsdocs.rocketsoftware.com/­bundle?labelkey=jbase_5.9
DeveloperApache Software Foundation, originally contributed from BaiduApache Software FoundationCrateRocket Software (formerly Zumasys)
Initial release2017201820131991
Current release1.2.2, February 20231.1.0, April 20235.8.1, August 20245.7
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Sourcecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJava
Server operating systemsLinuxAll OS with a Java VM (>= 1.8)All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportAIX
Linux
Windows
Data schemeyesyesFlexible Schema (defined schema, partial schema, schema free)schema-free
Typing infopredefined data types such as float or dateyesyesyesoptional
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 indexesyesyesyes
SQL infoSupport of SQLyesSQL-like query languageyes, but no triggers and constraints, and PostgreSQL compatibilityEmbedded SQL for jBASE in BASIC
APIs and other access methodsJDBC
MySQL client
JDBC
Native API
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API
Supported programming languagesJavaC
C#
C++
Go
Java
Python
Scala
.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
Basic
Jabbascript
Java
Server-side scripts infoStored proceduresuser defined functionsyesuser defined functions (Javascript)yes
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioninghorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasConfigurable replication on table/partition-levelyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoIntegration with Hadoop and Sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Read-after-write consistency on record level
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infounique row identifiers can be used for implementing an optimistic concurrency control strategyACID
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.noyesnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardyesrights management via user accountsAccess rights can be defined down to the item level

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More resources
Apache DorisApache IoTDBCrateDBjBASE
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