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DBMS > DolphinDB vs. HBase vs. IRONdb vs. Spark SQL vs. Transbase

System Properties Comparison DolphinDB vs. HBase vs. IRONdb vs. Spark SQL vs. Transbase

Editorial information provided by DB-Engines
NameDolphinDB  Xexclude from comparisonHBase  Xexclude from comparisonIRONdb  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionDolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.Wide-column store based on Apache Hadoop and on concepts of BigTableA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicitySpark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelTime Series DBMSWide column storeTime Series DBMSRelational DBMSRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.23
Rank#82  Overall
#6  Time Series DBMS
Score31.25
Rank#26  Overall
#2  Wide column stores
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score0.15
Rank#337  Overall
#147  Relational DBMS
Websitewww.dolphindb.comhbase.apache.orgwww.circonus.com/solutions/time-series-database/spark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationdocs.dolphindb.cn/­en/­help200/­index.htmlhbase.apache.org/­book.htmldocs.circonus.com/irondb/category/getting-startedspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperDolphinDB, IncApache Software Foundation infoApache top-level project, originally developed by PowersetCirconus LLC.Apache Software FoundationTransaction Software GmbH
Initial release20182008201720141987
Current releasev2.00.4, January 20222.3.4, January 2021V0.10.20, January 20183.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open Sourcecommercial infofree community version availableOpen Source infoApache version 2commercialOpen Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC and C++ScalaC and C++
Server operating systemsLinux
Windows
Linux
Unix
Windows infousing Cygwin
LinuxLinux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyesschema-free, schema definition possibleschema-freeyesyes
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyes infotext, numeric, histogramsyesyes
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.nonononono
Secondary indexesyesnononoyes
SQL infoSupport of SQLSQL-like query languagenoSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
Java API
RESTful HTTP API
Thrift
HTTP APIJDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesC#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresyesyes infoCoprocessors in Javayes, in Luanoyes
Triggersnoyesnonoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingAutomatic, metric affinity per nodeyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
configurable replication factor, datacenter awarenoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesSingle row ACID (across millions of columns)nonoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnonono
User concepts infoAccess controlAdministrators, Users, GroupsAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnonofine grained access rights according to SQL-standard

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More resources
DolphinDBHBaseIRONdbSpark SQLTransbase
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