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DBMS > EJDB vs. IRONdb vs. Kinetica vs. Tarantool

System Properties Comparison EJDB vs. IRONdb vs. Kinetica vs. Tarantool

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Editorial information provided by DB-Engines
NameEJDB  Xexclude from comparisonIRONdb  Xexclude from comparisonKinetica  Xexclude from comparisonTarantool  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionEmbeddable document-store database library with JSON representation of queries (in MongoDB style)A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityFully vectorized database across both GPUs and CPUsIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelDocument storeTime Series DBMSRelational DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Spatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.27
Rank#297  Overall
#44  Document stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Websitegithub.com/­Softmotions/­ejdbwww.circonus.com/solutions/time-series-database/www.kinetica.comwww.tarantool.io
Technical documentationgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mddocs.circonus.com/irondb/category/getting-starteddocs.kinetica.comwww.tarantool.io/­en/­doc
DeveloperSoftmotionsCirconus LLC.KineticaVK
Initial release2012201720122008
Current releaseV0.10.20, January 20187.1, August 20212.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoGPLv2commercialcommercialOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC and C++C, C++C and C++
Server operating systemsserver-lessLinuxLinuxBSD
Linux
macOS
Data schemeschema-freeschema-freeyesFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyes infostring, integer, double, bool, date, object_idyes infotext, numeric, histogramsyesstring, double, decimal, uuid, integer, blob, boolean, datetime
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 indexesnonoyesyes
SQL infoSupport of SQLnoSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like DML and DDL statementsFull-featured ANSI SQL support
APIs and other access methodsin-process shared libraryHTTP APIJDBC
ODBC
RESTful HTTP API
Open binary protocol
Supported programming languagesActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C++
Java
JavaScript (Node.js)
Python
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresnoyes, in Luauser defined functionsLua, C and SQL stored procedures
Triggersnonoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesnoneAutomatic, metric affinity per nodeShardingSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesnoneconfigurable replication factor, datacenter awareSource-replica replicationAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency per node, eventual consistency across nodesImmediate Consistency or Eventual Consistency depending on configurationCasual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Foreign keys infoReferential integrityno infotypically not needed, however similar functionality with collection joins possiblenoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayes infoRead/Write Lockingyesyesyes, cooperative multitasking
Durability infoSupport for making data persistentyesyesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAMyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlnonoAccess rights for users and roles on table levelAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources
EJDBIRONdbKineticaTarantool
DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021,  Vladimir Perepelytsya, Tarantool (sponsor) 

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