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DBMS > AnzoGraph DB vs. Apache IoTDB vs. CrateDB vs. TigerGraph

System Properties Comparison AnzoGraph DB vs. Apache IoTDB vs. CrateDB vs. TigerGraph

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Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonApache IoTDB  Xexclude from comparisonCrateDB  Xexclude from comparisonTigerGraph  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkDistributed Database based on LuceneA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelGraph DBMS
RDF store
Time Series DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Graph DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#302  Overall
#24  Graph DBMS
#13  RDF stores
Score1.31
Rank#159  Overall
#14  Time Series DBMS
Score0.69
Rank#226  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#11  Vector DBMS
Score1.44
Rank#152  Overall
#14  Graph DBMS
Websitecambridgesemantics.com/­anzographiotdb.apache.orgcratedb.comwww.tigergraph.com
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlcratedb.com/­docsdocs.tigergraph.com
DeveloperCambridge SemanticsApache Software FoundationCrate
Initial release2018201820132017
Current release2.3, January 20211.1.0, April 20235.8.1, August 2024
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoApache Version 2.0Open Sourcecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++
Server operating systemsLinuxAll OS with a Java VM (>= 1.8)All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinux
Data schemeSchema-free and OWL/RDFS-schema supportyesFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesyesyes
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 indexesnoyesyes
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.SQL-like query languageyes, but no triggers and constraints, and PostgreSQL compatibilitySQL-like query language (GSQL)
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
JDBC
Native API
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesC++
Java
Python
C
C#
C++
Go
Java
Python
Scala
.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
C++
Java
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesuser defined functions (Javascript)yes
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardinghorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-Clusterselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasConfigurable replication on table/partition-level
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingIntegration with Hadoop and Sparknoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Read-after-write consistency on record level
Foreign keys infoReferential integrityno infonot needed in graphsnonoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono infounique row identifiers can be used for implementing an optimistic concurrency control strategyACID
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.yesyesnono
User concepts infoAccess controlAccess rights for users and rolesyesrights management via user accountsRole-based access control

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More resources
AnzoGraph DBApache IoTDBCrateDBTigerGraph
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