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DBMS > AnzoGraph DB vs. Apache IoTDB vs. Google Cloud Spanner vs. Kinetica vs. SpaceTime

System Properties Comparison AnzoGraph DB vs. Apache IoTDB vs. Google Cloud Spanner vs. Kinetica vs. SpaceTime

Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonApache IoTDB  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonKinetica  Xexclude from comparisonSpaceTime  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 FlinkA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Fully vectorized database across both GPUs and CPUsSpaceTime is a spatio-temporal DBMS with a focus on performance.
Primary database modelGraph DBMS
RDF store
Time Series DBMSRelational DBMSRelational DBMSSpatial DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#307  Overall
#24  Graph DBMS
#13  RDF stores
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.00
Rank#383  Overall
#7  Spatial DBMS
Websitecambridgesemantics.com/­anzographiotdb.apache.orgcloud.google.com/­spannerwww.kinetica.comwww.mireo.com/­spacetime
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlcloud.google.com/­spanner/­docsdocs.kinetica.com
DeveloperCambridge SemanticsApache Software FoundationGoogleKineticaMireo
Initial release20182018201720122020
Current release2.3, January 20211.1.0, April 20237.1, August 2021
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoApache Version 2.0commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++C++
Server operating systemsLinuxAll OS with a Java VM (>= 1.8)hostedLinuxLinux
Data schemeSchema-free and OWL/RDFS-schema supportyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nonononono
Secondary indexesnoyesyesyesno
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.SQL-like query languageyes infoQuery statements complying to ANSI 2011SQL-like DML and DDL statementsA subset of ANSI SQL is implemented
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
JDBC
Native API
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
RESTful HTTP API
Supported programming languagesC++
Java
Python
C
C#
C++
Go
Java
Python
Scala
Go
Java
JavaScript (Node.js)
Python
C++
Java
JavaScript (Node.js)
Python
C#
C++
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesnouser defined functionsno
Triggersnoyesnoyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardinghorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingFixed-grid hypercubes
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 replicasMulti-source replication with 3 replicas for regional instances.Source-replica replicationReal-time block device replication (DRBD)
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingIntegration with Hadoop and Sparkyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityno infonot needed in graphsnoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoStrict serializable isolationnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes infoGPU vRAM or System RAMno
User concepts infoAccess controlAccess rights for users and rolesyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles on table levelyes

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More resources
AnzoGraph DBApache IoTDBGoogle Cloud SpannerKineticaSpaceTime
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