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DBMS > AnzoGraph DB vs. Hazelcast vs. Microsoft Azure Data Explorer vs. Oracle NoSQL vs. TerarkDB

System Properties Comparison AnzoGraph DB vs. Hazelcast vs. Microsoft Azure Data Explorer vs. Oracle NoSQL vs. TerarkDB

Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOracle NoSQL  Xexclude from comparisonTerarkDB  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationA widely adopted in-memory data gridFully managed big data interactive analytics platformA multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodesA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelGraph DBMS
RDF store
Key-value storeRelational DBMS infocolumn orientedDocument store
Key-value store
Relational DBMS
Key-value store
Secondary database modelsDocument store infoJSON support with IMDG 3.12Document store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#307  Overall
#24  Graph DBMS
#13  RDF stores
Score5.97
Rank#57  Overall
#6  Key-value stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score2.95
Rank#100  Overall
#17  Document stores
#17  Key-value stores
#50  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitecambridgesemantics.com/­anzographhazelcast.comazure.microsoft.com/­services/­data-explorerwww.oracle.com/­database/­nosql/­technologies/­nosqlgithub.com/­bytedance/­terarkdb
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmhazelcast.org/­imdg/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­en/­database/­other-databases/­nosql-database/­index.htmlbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperCambridge SemanticsHazelcastMicrosoftOracleByteDance, originally Terark
Initial release20182008201920112016
Current release2.3, January 20215.3.6, November 2023cloud service with continuous releases23.3, December 2023
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoProprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)commercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC++
Server operating systemsLinuxAll OS with a Java VMhostedLinux
Solaris SPARC/x86
Data schemeSchema-free and OWL/RDFS-schema supportschema-freeFixed schema with schema-less datatypes (dynamic)Support Fixed schema and Schema-less deployment with the ability to interoperate between them.schema-free
Typing infopredefined data types such as float or dateyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesoptionalno
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.noyes infothe object must implement a serialization strategyyesnono
Secondary indexesnoyesall fields are automatically indexedyesno
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.SQL-like query languageKusto Query Language (KQL), SQL subsetSQL-like DML and DDL statementsno
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
JCache
JPA
Memcached protocol
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP APIC++ API
Java API
Supported programming languagesC++
Java
Python
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C#
Go
Java
JavaScript (Node.js)
Python
C++
Java
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infoEvent Listeners, Executor ServicesYes, possible languages: KQL, Python, Rnono
Triggersnoyes infoEventsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingSharding infoImplicit feature of the cloud serviceShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-Clusteryes infoReplicated Mapyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Electable source-replica replication per shard. Support distributed global deployment with Multi-region table featurenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkwith Hadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency infodepending on configuration
Foreign keys infoReferential integrityno infonot needed in graphsnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitednoconfigurable infoACID within a storage node (=shard)no
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 infooff heap cacheyes
User concepts infoAccess controlAccess rights for users and rolesRole-based access controlAzure Active Directory AuthenticationAccess rights for users and rolesno

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More resources
AnzoGraph DBHazelcastMicrosoft Azure Data ExplorerOracle NoSQLTerarkDB
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