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DBMS > Apache IoTDB vs. ArangoDB vs. Microsoft Azure Table Storage vs. TigerGraph

System Properties Comparison Apache IoTDB vs. ArangoDB vs. Microsoft Azure Table Storage vs. TigerGraph

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonArangoDB  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonTigerGraph  Xexclude from comparison
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkNative multi-model DBMS for graph, document, key/value and search. All in one engine and accessible with one query language.A Wide Column Store for rapid development using massive semi-structured datasetsA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelTime Series DBMSDocument store
Graph DBMS
Key-value store
Search engine
Wide column storeGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score3.32
Rank#90  Overall
#15  Document stores
#5  Graph DBMS
#12  Key-value stores
#10  Search engines
Score4.48
Rank#75  Overall
#6  Wide column stores
Score1.83
Rank#139  Overall
#13  Graph DBMS
Websiteiotdb.apache.orgarangodb.comazure.microsoft.com/­en-us/­services/­storage/­tableswww.tigergraph.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.arangodb.comdocs.tigergraph.com
Social network pagesLinkedInTwitterFacebookYouTubeInstagram
DeveloperApache Software FoundationArangoDB Inc.Microsoft
Initial release2018201220122017
Current release1.1.0, April 20233.11.5, November 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2; Commercial license (Enterprise) availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Windows
hostedLinux
Data schemeyesschema-free infoautomatically recognizes schema within a collectionschema-freeyes
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 indexesyesyesno
SQL infoSupport of SQLSQL-like query languagenonoSQL-like query language (GSQL)
APIs and other access methodsJDBC
Native API
AQL
Foxx Framework
Graph API (Gremlin)
GraphQL query language
HTTP API
Java & SpringData
JSON style queries
VelocyPack/VelocyStream
RESTful HTTP APIGSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
C++
Clojure
Elixir
Go
Java
JavaScript (Node.js)
PHP
Python
R
Rust
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
Server-side scripts infoStored proceduresyesJavaScriptnoyes
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infosince version 2.0Sharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasSource-replica replication with configurable replication factoryes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkno infocan be done with stored procedures in JavaScriptnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency infoconfigurable per collection or per write
Immediate Consistency
OneShard (highly available, fault-tolerant deployment mode with ACID semantics)
Immediate Consistency
Foreign keys infoReferential integritynoyes inforelationships in graphsnoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDoptimistic lockingACID
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.yesnono
User concepts infoAccess controlyesyesAccess rights based on private key authentication or shared access signaturesRole-based access control
More information provided by the system vendor
Apache IoTDBArangoDBMicrosoft Azure Table StorageTigerGraph
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
Apache IoTDBArangoDBMicrosoft Azure Table StorageTigerGraph
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