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DBMS > Apache IoTDB vs. Axibase vs. Citus vs. Tarantool

System Properties Comparison Apache IoTDB vs. Axibase vs. Citus vs. Tarantool

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonAxibase  Xexclude from comparisonCitus  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkScalable TimeSeries DBMS based on HBase with integrated rule engine and visualizationScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelTime Series DBMSTime Series DBMSRelational DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsDocument storeSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.35
Rank#282  Overall
#25  Time Series DBMS
Score2.15
Rank#117  Overall
#56  Relational DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websiteiotdb.apache.orgaxibase.com/­docs/­atsd/­financewww.citusdata.comwww.tarantool.io
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.citusdata.comwww.tarantool.io/­en/­doc
DeveloperApache Software FoundationAxibase CorporationVK
Initial release2018201320102008
Current release1.1.0, April 2023155858.1, December 20182.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infoCommunity Edition (single node) is free, Enterprise Edition (distributed) is paidOpen Source infoAGPL, commercial license also availableOpen 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 languageJavaJavaCC and C++
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxLinuxBSD
Linux
macOS
Data schemeyesyesyesFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesyes infoshort, integer, long, float, double, decimal, stringyesstring, 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.nonoyes infospecific XML type available, but no XML query functionalityno
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like query languageSQL-like query languageyes infostandard, with numerous extensionsFull-featured ANSI SQL support
APIs and other access methodsJDBC
Native API
JDBC
Proprietary protocol (Network API)
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Open binary protocol
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Go
Java
PHP
Python
R
Ruby
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresyesyesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.Lua, C and SQL stored procedures
Triggersyesyesyesyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingSharding, 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 nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasSource-replica replicationSource-replica replication infoother methods possible by using 3rd party extensionsAsynchronous 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 methodsIntegration with Hadoop and Sparkyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyCasual 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 integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, 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.yesnoyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlyesfine grained access rights according to SQL-standardAccess 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
Apache IoTDBAxibaseCitusTarantool
DB-Engines blog posts

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

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