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DBMS > Heroic vs. Kinetica vs. Tarantool vs. TinkerGraph

System Properties Comparison Heroic vs. Kinetica vs. Tarantool vs. TinkerGraph

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Editorial information provided by DB-Engines
NameHeroic  Xexclude from comparisonKinetica  Xexclude from comparisonTarantool  Xexclude from comparisonTinkerGraph  Xexclude from comparison
DescriptionTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchFully vectorized database across both GPUs and CPUsIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsA lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API
Primary database modelTime Series DBMSRelational DBMSDocument store
Key-value store
Relational DBMS
Graph 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
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Score0.08
Rank#348  Overall
#35  Graph DBMS
Websitegithub.com/­spotify/­heroicwww.kinetica.comwww.tarantool.iotinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlin
Technical documentationspotify.github.io/­heroicdocs.kinetica.comwww.tarantool.io/­en/­doc
DeveloperSpotifyKineticaVK
Initial release2014201220082009
Current release7.1, August 20212.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool EnterpriseOpen Source infoApache 2.0
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 languageJavaC, C++C and C++Java
Server operating systemsLinuxBSD
Linux
macOS
Data schemeschema-freeyesFlexible data schema: relational definition for tables with ability to store json-like documents in columnsschema-free
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.nononono
Secondary indexesyes infovia Elasticsearchyesyesno
SQL infoSupport of SQLnoSQL-like DML and DDL statementsFull-featured ANSI SQL supportno
APIs and other access methodsHQL (Heroic Query Language, a JSON-based language)
HTTP API
JDBC
ODBC
RESTful HTTP API
Open binary protocolTinkerPop 3
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Groovy
Java
Server-side scripts infoStored proceduresnouser defined functionsLua, C and SQL stored proceduresno
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes, before/after data modification events, on replication events, client session eventsno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.none
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate 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
none
Foreign keys infoReferential integritynoyesyesyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactionsno
Concurrency infoSupport for concurrent manipulation of datayesyesyes, cooperative multitaskingno
Durability infoSupport for making data persistentyesyesyes, write ahead loggingoptional
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 persistenceyes
User concepts infoAccess controlAccess 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
no

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More resources
HeroicKineticaTarantoolTinkerGraph
DB-Engines blog posts

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

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