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DBMS > AgensGraph vs. Dgraph vs. JanusGraph vs. Tarantool

System Properties Comparison AgensGraph vs. Dgraph vs. JanusGraph vs. Tarantool

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Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonDgraph  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLDistributed and scalable native Graph DBMSA Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017In-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelGraph DBMS
Relational DBMS
Graph DBMSGraph DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.20
Rank#321  Overall
#27  Graph DBMS
#143  Relational DBMS
Score1.45
Rank#156  Overall
#15  Graph DBMS
Score1.94
Rank#129  Overall
#12  Graph DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Websitebitnine.net/­agensgraphdgraph.iojanusgraph.orgwww.tarantool.io
Technical documentationbitnine.net/­documentationdgraph.io/­docsdocs.janusgraph.orgwww.tarantool.io/­en/­doc
DeveloperBitnine Global Inc.Dgraph Labs, Inc.Linux Foundation; originally developed as Titan by AureliusVK
Initial release2016201620172008
Current release2.1, December 20180.6.3, February 20232.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoApache License 2.0Open Source infoApache 2.0Open Source infoApache 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 languageCGoJavaC and C++
Server operating systemsLinux
OS X
Windows
Linux
OS X
Windows
Linux
OS X
Unix
Windows
BSD
Linux
macOS
Data schemedepending on used data modelschema-freeyesFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesyesyesstring, 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 indexesyesyesyesyes
SQL infoSupport of SQLyesnonoFull-featured ANSI SQL support
APIs and other access methodsCypher Query Language
JDBC
GraphQL query language
gRPC (using protocol buffers) API
HTTP API
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Open binary protocol
Supported programming languagesC
Java
JavaScript
Python
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Clojure
Java
Python
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresyesnoyesLua, C and SQL stored procedures
Triggersnonoyesyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritanceyesyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)Sharding, 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 nodesSource-replica replicationSynchronous replication via RaftyesAsynchronous 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 methodsnonoyes infovia Faunus, a graph analytics engine
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Casual 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 integrityyesnoyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID, 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 persistentyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyes, 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 controlfine grained access rights according to SQL-standardno infoPlanned for future releasesUser authentification and security via Rexster Graph ServerAccess 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
AgensGraphDgraphJanusGraph infosuccessor of TitanTarantool
DB-Engines blog posts

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

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