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DBMS > DolphinDB vs. etcd vs. HEAVY.AI vs. jBASE vs. Kinetica

System Properties Comparison DolphinDB vs. etcd vs. HEAVY.AI vs. jBASE vs. Kinetica

Editorial information provided by DB-Engines
NameDolphinDB  Xexclude from comparisonetcd  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonjBASE  Xexclude from comparisonKinetica  Xexclude from comparison
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.A distributed reliable key-value storeA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareA robust multi-value DBMS comprising development tools and middlewareFully vectorized database across both GPUs and CPUs
Primary database modelTime Series DBMS
Vector DBMS
Key-value storeRelational DBMSMultivalue DBMSRelational DBMS
Secondary database modelsRelational DBMSSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.60
Rank#102  Overall
#8  Time Series DBMS
#6  Vector DBMS
Score7.20
Rank#46  Overall
#5  Key-value stores
Score1.34
Rank#156  Overall
#72  Relational DBMS
Score1.39
Rank#154  Overall
#3  Multivalue DBMS
Score0.42
Rank#257  Overall
#120  Relational DBMS
Websitewww.dolphindb.cometcd.io
github.com/­etcd-io/­etcd
github.com/­heavyai/­heavydb
www.heavy.ai
www.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-jbasewww.kinetica.com
Technical documentationdocs.dolphindb.cn/­en/­help200/­index.htmletcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.heavy.aidocs.rocketsoftware.com/­bundle?labelkey=jbase_5.9docs.kinetica.com
DeveloperDolphinDB, IncHEAVY.AI, Inc.Rocket Software (formerly Zumasys)Kinetica
Initial release2018201619912012
Current releasev2.00.4, January 20223.4, August 20195.10, January 20225.77.1, August 2021
License infoCommercial or Open Sourcecommercial infofree community version availableOpen Source infoApache Version 2.0Open Source infoApache Version 2; enterprise edition availablecommercialcommercial
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++GoC++ and CUDAC, C++
Server operating systemsLinux
Windows
FreeBSD
Linux
Windows infoexperimental
LinuxAIX
Linux
Windows
Linux
Data schemeyesschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesnoyesoptionalyes
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.nononoyesno
Secondary indexesyesnonoyes
SQL infoSupport of SQLSQL-like query languagenoyesEmbedded SQL for jBASE in BASICSQL-like DML and DDL statements
APIs and other access methodsJDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
gRPC
JSON over HTTP
JDBC
ODBC
Thrift
Vega
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
All languages supporting JDBC/ODBC/Thrift
Python
.Net
Basic
Jabbascript
Java
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesnonoyesuser defined functions
Triggersnoyes, watching key changesnoyesyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding infoRound robinShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replicationyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnonoACIDno
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.yesnoyesyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlAdministrators, Users, Groupsnofine grained access rights according to SQL-standardAccess rights can be defined down to the item levelAccess rights for users and roles on table level

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More resources
DolphinDBetcdHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022jBASEKinetica
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