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DBMS > Heroic vs. SpaceTime vs. Tarantool vs. Titan vs. ToroDB

System Properties Comparison Heroic vs. SpaceTime vs. Tarantool vs. Titan vs. ToroDB

Editorial information provided by DB-Engines
NameHeroic  Xexclude from comparisonSpaceTime  Xexclude from comparisonTarantool  Xexclude from comparisonTitan  Xexclude from comparisonToroDB  Xexclude from comparison
Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchSpaceTime is a spatio-temporal DBMS with a focus on performance.In-memory computing platform with a flexible data schema for efficiently building high-performance applicationsTitan is a Graph DBMS optimized for distributed clusters.A MongoDB-compatible JSON document store, built on top of PostgreSQL
Primary database modelTime Series DBMSSpatial DBMSDocument store
Key-value store
Relational DBMS
Graph DBMSDocument store
Secondary database modelsRelational DBMSSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score0.03
Rank#392  Overall
#8  Spatial DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websitegithub.com/­spotify/­heroicwww.mireo.com/­spacetimewww.tarantool.iogithub.com/­thinkaurelius/­titangithub.com/­torodb/­server
Technical documentationspotify.github.io/­heroicwww.tarantool.io/­en/­docgithub.com/­thinkaurelius/­titan/­wiki
DeveloperSpotifyMireoVKAurelius, owned by DataStax8Kdata
Initial release20142020200820122016
Current release2.10.0, 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 license, version 2.0Open Source infoAGPL-V3
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C and C++JavaJava
Server operating systemsLinuxBSD
Linux
macOS
Linux
OS X
Unix
Windows
All OS with a Java 7 VM
Data schemeschema-freeyesFlexible data schema: relational definition for tables with ability to store json-like documents in columnsyesschema-free
Typing infopredefined data types such as float or dateyesyesstring, double, decimal, uuid, integer, blob, boolean, datetimeyesyes infostring, integer, double, boolean, date, object_id
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 Elasticsearchnoyesyes
SQL infoSupport of SQLnoA subset of ANSI SQL is implementedFull-featured ANSI SQL supportno
APIs and other access methodsHQL (Heroic Query Language, a JSON-based language)
HTTP API
RESTful HTTP APIOpen binary protocolJava API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Supported programming languagesC#
C++
Python
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Clojure
Java
Python
Server-side scripts infoStored proceduresnonoLua, C and SQL stored proceduresyes
Triggersnonoyes, before/after data modification events, on replication events, client session eventsyesno
Partitioning methods infoMethods for storing different data on different nodesShardingFixed-grid hypercubesSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.yes infovia pluggable storage backendsSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesReal-time block device replication (DRBD)Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
yesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infovia Faunus, a graph analytics engine
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
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
Eventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesyes infoRelationships in graphno
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 transactionsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes, cooperative multitaskingyesyes
Durability infoSupport for making data persistentyesyesyes, write ahead loggingyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlyesAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
User authentification and security via Rexster Graph ServerAccess rights for users and roles

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More resources
HeroicSpaceTimeTarantoolTitanToroDB
DB-Engines blog posts

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

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Graph DBMS increased their popularity by 500% within the last 2 years
3 March 2015, Paul Andlinger

Graph DBMSs are gaining in popularity faster than any other database category
21 January 2014, Matthias Gelbmann

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