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DBMS > AnzoGraph DB vs. Faircom EDGE vs. Hazelcast vs. Ingres vs. Microsoft Azure Data Explorer

System Properties Comparison AnzoGraph DB vs. Faircom EDGE vs. Hazelcast vs. Ingres vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonHazelcast  Xexclude from comparisonIngres  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 virtualizationFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsA widely adopted in-memory data gridWell established RDBMSFully managed big data interactive analytics platform
Primary database modelGraph DBMS
RDF store
Key-value store
Relational DBMS
Key-value storeRelational DBMSRelational 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
Score0.29
Rank#303  Overall
#25  Graph DBMS
#14  RDF stores
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score3.80
Rank#82  Overall
#44  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websitecambridgesemantics.com/­anzographwww.faircom.com/­products/­faircom-edgehazelcast.comwww.actian.com/­databases/­ingresazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlhazelcast.org/­imdg/­docsdocs.actian.com/­ingresdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperCambridge SemanticsFairCom CorporationHazelcastActian CorporationMicrosoft
Initial release2018197920081974 infooriginally developed at University Berkely in early 1970s2019
Current release2.3, January 2021V3, October 20205.3.6, November 202311.2, May 2022cloud service with continuous releases
License infoCommercial or Open Sourcecommercial infofree trial version availablecommercial infoRestricted, free version availableOpen Source infoApache Version 2; commercial licenses availablecommercialcommercial
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 languageANSI C, C++JavaC
Server operating systemsLinuxAndroid
Linux infoARM, x86
Raspbian
Windows
All OS with a Java VMAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
hosted
Data schemeSchema-free and OWL/RDFS-schema supportFlexible Schema (defined schema, partial schema, schema free)schema-freeyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyes, ANSI Standard SQL Typesyesyesyes 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.noyesyes infothe object must implement a serialization strategyno infobut tools for importing/exporting data from/to XML-files availableyes
Secondary indexesnoyesyesyesall fields are automatically indexed
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.yes infoANSI SQL queriesSQL-like query languageyesKusto 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
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC++
Java
Python
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
.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 aggregatesyes info.Net, JavaScript, C/C++yes infoEvent Listeners, Executor ServicesyesYes, possible languages: KQL, Python, R
Triggersnoyesyes infoEventsyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingFile partitioning infoCustomizable business rules for partitioningShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-Clusteryes infoSynchronous and asynchronous realtime replication based on transaction logsyes infoReplicated MapIngres Replicatoryes 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 loadingnoyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterImmediate Consistency
Tunable Consistency
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityno infonot needed in graphsyes infowhen using SQLnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDone or two-phase-commit; repeatable reads; read commitedACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesyes infoMVCCyes
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.yesyesyesnono
User concepts infoAccess controlAccess rights for users and rolesFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Role-based access controlfine grained access rights according to SQL-standardAzure Active Directory Authentication

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More resources
AnzoGraph DBFaircom EDGE infoformerly c-treeEDGEHazelcastIngresMicrosoft Azure Data Explorer
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