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DBMS > Amazon DocumentDB vs. ArangoDB vs. HugeGraph vs. TigerGraph

System Properties Comparison Amazon DocumentDB vs. ArangoDB vs. HugeGraph vs. TigerGraph

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonArangoDB  Xexclude from comparisonHugeGraph  Xexclude from comparisonTigerGraph  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceNative multi-model DBMS for graph, document, key/value and search. All in one engine and accessible with one query language.A fast-speed and highly-scalable Graph DBMSA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelDocument storeDocument store
Graph DBMS
Key-value store
Search engine
Graph DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score3.26
Rank#88  Overall
#15  Document stores
#5  Graph DBMS
#12  Key-value stores
#10  Search engines
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score1.80
Rank#138  Overall
#13  Graph DBMS
Websiteaws.amazon.com/­documentdbarangodb.comgithub.com/­hugegraph
hugegraph.apache.org
www.tigergraph.com
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.arangodb.comhugegraph.apache.org/­docsdocs.tigergraph.com
Social network pagesLinkedInTwitterYouTubeFacebookInstagram
DeveloperArangoDB Inc.Baidu
Initial release2019201220182017
Current release3.11.5, November 20230.9
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; Commercial license (Enterprise) availableOpen Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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ArangoDB Cloud –The Managed Cloud Service of ArangoDB. 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++JavaC++
Server operating systemshostedLinux
OS X
Windows
Linux
macOS
Unix
Linux
Data schemeschema-freeschema-free infoautomatically recognizes schema within a collectionyesyes
Typing infopredefined data types such as float or dateyesyes 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.nonono
Secondary indexesyesyesyes infoalso supports composite index and range index
SQL infoSupport of SQLnononoSQL-like query language (GSQL)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)AQL
Foxx Framework
Graph API (Gremlin)
GraphQL query language
HTTP API
Java & SpringData
JSON style queries
VelocyPack/VelocyStream
Java API
RESTful HTTP API
TinkerPop Gremlin
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C#
C++
Clojure
Elixir
Go
Java
JavaScript (Node.js)
PHP
Python
R
Rust
Groovy
Java
Python
C++
Java
Server-side scripts infoStored proceduresnoJavaScriptasynchronous Gremlin script jobsyes
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infosince version 2.0yes infodepending on used storage backend, e.g. Cassandra and HBase
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasSource-replica replication with configurable replication factoryes infodepending on used storage backend, e.g. Cassandra and HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)no infocan be done with stored procedures in JavaScriptvia hugegraph-sparkyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoconfigurable per collection or per write
Immediate Consistency
OneShard (highly available, fault-tolerant deployment mode with ACID semantics)
Eventual Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyes inforelationships in graphsyes infoedges in graphyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlAccess rights for users and rolesyesUsers, roles and permissionsRole-based access control
More information provided by the system vendor
Amazon DocumentDBArangoDBHugeGraphTigerGraph
Specific characteristicsGraph and Beyond. With more than 11,000 stargazers on GitHub, ArangoDB is the leading...
» more
Competitive advantagesConsolidation: As a native multi-model database, can be used as a full blown document...
» more
Typical application scenariosNative multi-model in ArangoDB is being used for a broad range of projects across...
» more
Key customersCisco, Barclays, Refinitive, Siemens Mentor, Kabbage, Liaison, Douglas, MakeMyTrip,...
» more
Market metricsArangoDB is the leading native multi-model database with over 11,000 stargazers on...
» more
Licensing and pricing modelsVery permissive Apache 2 License for Community Edition & commercial licenses are...
» more

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More resources
Amazon DocumentDBArangoDBHugeGraphTigerGraph
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The Weight of Relational Databases: Time for Multi-Model?
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