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DBMS > Fujitsu Enterprise Postgres vs. Hazelcast vs. Ingres vs. Microsoft Azure Data Explorer vs. Microsoft Azure Table Storage

System Properties Comparison Fujitsu Enterprise Postgres vs. Hazelcast vs. Ingres vs. Microsoft Azure Data Explorer vs. Microsoft Azure Table Storage

Editorial information provided by DB-Engines
NameFujitsu Enterprise Postgres  Xexclude from comparisonHazelcast  Xexclude from comparisonIngres  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
DescriptionEnterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.A widely adopted in-memory data gridWell established RDBMSFully managed big data interactive analytics platformA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelRelational DBMSKey-value storeRelational DBMSRelational DBMS infocolumn orientedWide column store
Secondary database modelsDocument store
Spatial DBMS
Document 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
Score0.37
Rank#278  Overall
#128  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
Score4.04
Rank#77  Overall
#6  Wide column stores
Websitewww.postgresql.fastware.comhazelcast.comwww.actian.com/­databases/­ingresazure.microsoft.com/­services/­data-explorerazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationwww.postgresql.fastware.com/­product-manualshazelcast.org/­imdg/­docsdocs.actian.com/­ingresdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyHazelcastActian CorporationMicrosoftMicrosoft
Initial release20081974 infooriginally developed at University Berkely in early 1970s20192012
Current releaseFujitsu Enterprise Postgres 14, January 20225.3.6, November 202311.2, May 2022cloud service with continuous releases
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availablecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJavaC
Server operating systemsLinux
Windows
All OS with a Java VMAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
hostedhosted
Data schemeyesschema-freeyesFixed schema with schema-less datatypes (dynamic)schema-free
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-typesyes
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.yes infothe object must implement a serialization strategyno infobut tools for importing/exporting data from/to XML-files availableyesno
Secondary indexesyesyesyesall fields are automatically indexedno
SQL infoSupport of SQLyesSQL-like query languageyesKusto Query Language (KQL), SQL subsetno
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
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
RESTful HTTP API
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsyes infoEvent Listeners, Executor ServicesyesYes, possible languages: KQL, Python, Rno
Triggersyesyes infoEventsyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodespartitioning by range, list and by hashShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding infoImplicit feature of the cloud serviceSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoReplicated MapIngres Replicatoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitedACIDnooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyes infoMVCCyesyes
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.yesnonono
User concepts infoAccess controlfine grained access rights according to SQL-standardRole-based access controlfine grained access rights according to SQL-standardAzure Active Directory AuthenticationAccess rights based on private key authentication or shared access signatures

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More resources
Fujitsu Enterprise PostgresHazelcastIngresMicrosoft Azure Data ExplorerMicrosoft Azure Table Storage
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