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DBMS > BigObject vs. Cachelot.io vs. Kinetica vs. Tarantool

System Properties Comparison BigObject vs. Cachelot.io vs. Kinetica vs. Tarantool

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonCachelot.io  Xexclude from comparisonKinetica  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesIn-memory caching systemFully vectorized database across both GPUs and CPUsIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedKey-value storeRelational 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
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Websitebigobject.iocachelot.iowww.kinetica.comwww.tarantool.io
Technical documentationdocs.bigobject.iodocs.kinetica.comwww.tarantool.io/­en/­doc
DeveloperBigObject, Inc.KineticaVK
Initial release2015201520122008
Current release7.1, August 20212.10.0, May 2022
License infoCommercial or Open Sourcecommercial infofree community edition availableOpen Source infoSimplified BSD LicensecommercialOpen 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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C, 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)
FreeBSD
Linux
OS X
LinuxBSD
Linux
macOS
Data schemeyesschema-freeyesFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesnoyesstring, 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.nononono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like DML and DDL statementsFull-featured ANSI SQL support
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
Memcached protocolJDBC
ODBC
RESTful HTTP API
Open binary protocol
Supported programming languages.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresLuanouser 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 nodesnonenoneShardingSharding, 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 nodesnonenoneSource-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 systemnonenoneImmediate 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 integrityyes infoautomatically between fact table and dimension tablesnoyesyes
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 lock on objects (tables, trees)yesyesyes, cooperative multitasking
Durability infoSupport for making data persistentyesnoyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes 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
BigObjectCachelot.ioKineticaTarantool
DB-Engines blog posts

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

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