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DBMS > BigObject vs. Citus vs. Tarantool vs. Transbase

System Properties Comparison BigObject vs. Citus vs. Tarantool vs. Transbase

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonCitus  Xexclude from comparisonTarantool  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesScalable 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 applicationsA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedRelational DBMSDocument store
Key-value store
Relational DBMS
Relational DBMS
Secondary database modelsDocument storeSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Score0.11
Rank#341  Overall
#150  Relational DBMS
Websitebigobject.iowww.citusdata.comwww.tarantool.iowww.transaction.de/­en/­products/­transbase.html
Technical documentationdocs.bigobject.iodocs.citusdata.comwww.tarantool.io/­en/­docwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperBigObject, Inc.VKTransaction Software GmbH
Initial release2015201020081987
Current release8.1, December 20182.10.0, May 2022Transbase 8.3, 2022
License infoCommercial or Open Sourcecommercial infofree community edition availableOpen Source infoAGPL, commercial license also availableOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprisecommercial infofree development license
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 and C++
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
LinuxBSD
Linux
macOS
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyesyesFlexible data schema: relational definition for tables with ability to store json-like documents in columnsyes
Typing infopredefined data types such as float or dateyesyesstring, double, decimal, uuid, integer, blob, boolean, datetimeyes
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.noyes infospecific XML type available, but no XML query functionalitynono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infostandard, with numerous extensionsFull-featured ANSI SQL supportyes
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Open binary protocolADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresLuauser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.Lua, C and SQL stored proceduresyes
Triggersnoyesyes, before/after data modification events, on replication events, client session eventsyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding, 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 nodesnoneSource-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)
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate 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
Immediate Consistency
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactionsyes
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyes, cooperative multitaskingyes
Durability infoSupport for making data persistentyesyesyes, write ahead loggingyes
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 persistenceno
User concepts infoAccess controlnofine 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
fine grained access rights according to SQL-standard

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More resources
BigObjectCitusTarantoolTransbase
DB-Engines blog posts

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

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