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DBMS > AnzoGraph DB vs. BigObject vs. InfinityDB vs. Kinetica

System Properties Comparison AnzoGraph DB vs. BigObject vs. InfinityDB vs. Kinetica

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Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonBigObject  Xexclude from comparisonInfinityDB  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationAnalytic DBMS for real-time computations and queriesA Java embedded Key-Value Store which extends the Java Map interfaceFully vectorized database across both GPUs and CPUs
Primary database modelGraph DBMS
RDF store
Relational DBMS infoa hierachical model (tree) can be imposedKey-value storeRelational DBMS
Secondary database modelsSpatial DBMS
Time Series 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
Score0.13
Rank#329  Overall
#147  Relational DBMS
Score0.00
Rank#383  Overall
#59  Key-value stores
Score0.42
Rank#261  Overall
#120  Relational DBMS
Websitecambridgesemantics.com/­anzographbigobject.ioboilerbay.comwww.kinetica.com
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmdocs.bigobject.ioboilerbay.com/­infinitydb/­manualdocs.kinetica.com
DeveloperCambridge SemanticsBigObject, Inc.Boiler Bay Inc.Kinetica
Initial release2018201520022012
Current release2.3, January 20214.07.1, August 2021
License infoCommercial or Open Sourcecommercial infofree trial version availablecommercial infofree community edition availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++
Server operating systemsLinuxLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
All OS with a Java VMLinux
Data schemeSchema-free and OWL/RDFS-schema supportyesyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeyes
Typing infopredefined data types such as float or dateyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyes
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 indexesnoyesno infomanual creation possible, using inversions based on multi-value capabilityyes
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.SQL-like DML and DDL statementsnoSQL-like DML and DDL statements
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
fluentd
ODBC
RESTful HTTP API
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC++
Java
Python
JavaC++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesLuanouser defined functions
Triggersnononoyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingnonenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-ClusternonenoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusternoneImmediate Consistency infoREAD-COMMITTED or SERIALIZEDImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityno infonot needed in graphsyes infoautomatically between fact table and dimension tablesno infomanual creation possible, using inversions based on multi-value capabilityyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoOptimistic locking for transactions; no isolation for bulk loadsno
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yesyes
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.yesyesnoyes infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users and rolesnonoAccess rights for users and roles on table level

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More resources
AnzoGraph DBBigObjectInfinityDBKinetica
Recent citations in the news

AnzoGraph: A graph database for deep analytics
15 April 2019, InfoWorld

Cambridge Semantics Fits AnzoGraph DB with More Speed, Free Access
23 January 2020, Solutions Review

AnzoGraph: A W3C Standards-Based Graph Database | by Jo Stichbury
8 February 2019, Towards Data Science

Cambridge Semantics Unveils AnzoGraph DB with Geospatial Analytics
19 June 2020, Solutions Review

AWS Launches New Analytics Engine That Combines the Power Of Vector Search And Graph Data
1 December 2023, EnterpriseAI

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Kinetica Elevates RAG with Fast Access to Real-Time Data
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21 March 2024, insideBIGDATA

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18 March 2024, SiliconANGLE News

Kinetica: AI is a ‘killer app’ for data analytics
2 May 2023, Blocks & Files

Kinetica Taps Dell for Hardware
12 June 2018, Finovate

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