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DBMS > JanusGraph vs. NSDb vs. ObjectBox vs. Tarantool

System Properties Comparison JanusGraph vs. NSDb vs. ObjectBox vs. Tarantool

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Editorial information provided by DB-Engines
NameJanusGraph infosuccessor of Titan  Xexclude from comparisonNSDb  Xexclude from comparisonObjectBox  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionA Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesExtremely fast embedded database for small devices, IoT and MobileIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelGraph DBMSTime Series DBMSObject oriented DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsTime Series DBMSSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.94
Rank#129  Overall
#12  Graph DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score1.20
Rank#170  Overall
#5  Object oriented DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Websitejanusgraph.orgnsdb.ioobjectbox.iowww.tarantool.io
Technical documentationdocs.janusgraph.orgnsdb.io/­Architecturedocs.objectbox.iowww.tarantool.io/­en/­doc
DeveloperLinux Foundation; originally developed as Titan by AureliusObjectBox LimitedVK
Initial release2017201720172008
Current release0.6.3, February 20232.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2.0Open Source infoApache License 2.0Open 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 languageJavaJava, ScalaC and C++C and C++
Server operating systemsLinux
OS X
Unix
Windows
Linux
macOS
Android
iOS
Linux
macOS
Windows
BSD
Linux
macOS
Data schemeyesyesFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesyes: int, bigint, 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.nononono
Secondary indexesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLnoSQL-like query languagenoFull-featured ANSI SQL support
APIs and other access methodsJava API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
gRPC
HTTP REST
WebSocket
Proprietary native APIOpen binary protocol
Supported programming languagesClojure
Java
Python
Java
Scala
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresyesnonoLua, C and SQL stored procedures
Triggersyesnoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)ShardingnoneSharding, 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 nodesyesonline/offline synchronization between client and serverAsynchronous 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 methodsyes infovia Faunus, a graph analytics enginenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate 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 integrityyes infoRelationships in graphsnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID, 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 persistentyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, HazelcastUsing Apache Luceneyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlUser authentification and security via Rexster Graph ServeryesAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
More information provided by the system vendor
JanusGraph infosuccessor of TitanNSDbObjectBoxTarantool
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More resources
JanusGraph infosuccessor of TitanNSDbObjectBoxTarantool
DB-Engines blog posts

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

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Recent citations in the news

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JanusGraph Picks Up Where TitanDB Left Off
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