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DBMS > AnzoGraph DB vs. GBase vs. Hawkular Metrics vs. Hazelcast vs. Microsoft Azure Data Explorer

System Properties Comparison AnzoGraph DB vs. GBase vs. Hawkular Metrics vs. Hazelcast vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonGBase  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationWidely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A widely adopted in-memory data gridFully managed big data interactive analytics platform
Primary database modelGraph DBMS
RDF store
Relational DBMSTime Series DBMSKey-value storeRelational DBMS infocolumn oriented
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
Score1.07
Rank#185  Overall
#86  Relational DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitecambridgesemantics.com/­anzographwww.gbase.cnwww.hawkular.orghazelcast.comazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmwww.hawkular.org/­hawkular-metrics/­docs/­user-guidehazelcast.org/­imdg/­docsdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperCambridge SemanticsGeneral Data Technology Co., Ltd.Community supported by Red HatHazelcastMicrosoft
Initial release20182004201420082019
Current release2.3, January 2021GBase 8a, GBase 8s, GBase 8c5.3.6, November 2023cloud service with continuous releases
License infoCommercial or Open Sourcecommercial infofree trial version availablecommercialOpen Source infoApache 2.0Open Source infoApache Version 2; commercial licenses availablecommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, Java, PythonJavaJava
Server operating systemsLinuxLinuxLinux
OS X
Windows
All OS with a Java VMhosted
Data schemeSchema-free and OWL/RDFS-schema supportyesschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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.noyesnoyes infothe object must implement a serialization strategyyes
Secondary indexesnoyesnoyesall fields are automatically indexed
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.Standard with numerous extensionsnoSQL-like query languageKusto Query Language (KQL), SQL subset
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
ADO.NET
C API
JDBC
ODBC
HTTP RESTJCache
JPA
Memcached protocol
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC++
Java
Python
C#Go
Java
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functionsnoyes infoEvent Listeners, Executor ServicesYes, possible languages: KQL, Python, R
Triggersnoyesyes infovia Hawkular Alertingyes infoEventsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardinghorizontal partitioning (by range, list and hash) and vertical partitioningSharding infobased on CassandraShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-Clusteryesselectable replication factor infobased on Cassandrayes infoReplicated Mapyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingnoyesSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityno infonot needed in graphsyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoone or two-phase-commit; repeatable reads; read commitedno
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.yesnoyesno
User concepts infoAccess controlAccess rights for users and rolesyesnoRole-based access controlAzure Active Directory Authentication

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More resources
AnzoGraph DBGBaseHawkular MetricsHazelcastMicrosoft Azure Data Explorer
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