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DBMS > ArangoDB vs. Memgraph vs. TigerGraph

System Properties Comparison ArangoDB vs. Memgraph vs. TigerGraph

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Editorial information provided by DB-Engines
NameArangoDB  Xexclude from comparisonMemgraph  Xexclude from comparisonTigerGraph  Xexclude from comparison
DescriptionNative multi-model DBMS for graph, document, key/value and search. All in one engine and accessible with one query language.A hybrid, in-memory first, distributed graph DBMS delivering high-performance on analytical and transactional workloads at enterprise scaleA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelDocument store
Graph DBMS
Key-value store
Search engine
Graph DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.38
Rank#76  Overall
#10  Document stores
#3  Graph DBMS
#11  Key-value stores
#8  Search engines
Score0.24
Rank#280  Overall
#24  Graph DBMS
Score1.74
Rank#123  Overall
#9  Graph DBMS
Websitewww.arangodb.commemgraph.comwww.tigergraph.com
Technical documentationwww.arangodb.com/­docs/­stabledocs.memgraph.comdocs.tigergraph.com
DeveloperArangoDB Inc.Memgraph Ltd
Initial release201220172017
Current release3.7.9, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial license (Enterprise) availablecommercial infoFree license availablecommercial
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
ArangoDB Oasis –The Managed Cloud Service of ArangoDB. Oasis provides fully managed, and monitored cluster deployments of any size, with enterprise-grade security. Get started for free and continue for as little as $0,21/hour.
Implementation languageC++C and C++C++
Server operating systemsLinux
OS X
Windows
LinuxLinux
Data schemeschema-free infoautomatically recognizes schema within a collectionschema-free and schema-optionalyes
Typing infopredefined data types such as float or dateyes infostring, double, boolean, list, hashyesyes
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.nono
Secondary indexesyes
SQL infoSupport of SQLnonoSQL-like query language (GSQL)
APIs and other access methodsAQL
Foxx Framework
Graph API (Gremlin)
GraphQL query language
HTTP API
Java & SpringData
JSON style queries
VelocyPack/VelocyStream
Bolt protocol
Cypher query language
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesC#
C++
Clojure
Elixir
Go
Java
JavaScript (Node.js)
PHP
Python
R
Rust
.Net
C
C++
Elixir
Go
Haskell
Java
JavaScript
PHP
Python
Ruby
Scala
C++
Java
Server-side scripts infoStored proceduresJavaScriptyes
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesSharding infosince version 2.0Sharding infodynamic graph partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication with configurable replication factorMulti-source replication using RAFT
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infocan be done with stored procedures in JavaScriptnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoconfigurable per collection or per write
Immediate Consistency
OneShard (highly available, fault-tolerant deployment mode with ACID semantics)
Immediate Consistency
Foreign keys infoReferential integrityyes inforelationships in graphsyes inforelationships in graphsyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infowith snapshot isolationACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyes infowith periodic snapshot and write-ahead logging (WAL) of changesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlyesUsers, roles and permissionsRole-based access control
More information provided by the system vendor
ArangoDBMemgraphTigerGraph
Specific characteristicsOne Engine. One Query Language. Multiple Data Models. ArangoDB is an open source...
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TigerGraph is a native graph database, with massively parallel processing and fully...
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Competitive advantagesConsolidation: As a native multi-model database, can be used as a full blown document...
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TigerGraph is the fastest and most scalable graph platform, powered by a native parallel...
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Typical application scenariosNative multi-model in ArangoDB is being used for a broad range of projects across...
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Anti Money Laundering Real-Time Fraud Detection Customer 360 Real-Time Personalized...
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Key customersCisco, Barclays, Refinitive, Siemens Mentor, Kabbage, Liaison, Douglas, MakeMyTrip,...
» more
Four out of the top five global banks use TigerGraph for real-time fraud detection....
» more
Market metricsArangoDB is the leading native multi-model database with over 9000 stargazers on...
» more
ANALYST RESEARCH Nov 2020: TigerGraph Named A Leader For Graph Data Platforms - TigerGraph...
» more
Licensing and pricing modelsVery permissive Apache 2 License for Community Edition & commercial licenses are...
» more
Try TigerGraph for Free in the Cloud or On Prem https://www.tigergraph.com/get-tigergraph/...
» more
News

C++ Memory Model: Migrating from X86 to ARM
15 February 2021

What’s the Latest with ArangoDB?
29 January 2021

ArangoML Series: Multi-Model Collaboration
26 January 2021

State of the Art Preprocessing and Filtering with ArangoSearch
10 December 2020

ArangoML Series: Intro to NetworkX Adapter
17 November 2020

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
ArangoDBMemgraphTigerGraph
DB-Engines blog posts

The Weight of Relational Databases: Time for Multi-Model?
29 August 2017, Luca Olivari (guest author)

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