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DBMS > GigaSpaces vs. Greenplum vs. Microsoft Azure Data Explorer vs. Postgres-XL vs. TimesTen

System Properties Comparison GigaSpaces vs. Greenplum vs. Microsoft Azure Data Explorer vs. Postgres-XL vs. TimesTen

Editorial information provided by DB-Engines
NameGigaSpaces  Xexclude from comparisonGreenplum  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPostgres-XL  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.Fully managed big data interactive analytics platformBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresIn-Memory RDBMS compatible to Oracle
Primary database modelDocument store
Object oriented DBMS infoValues are user defined objects
Relational DBMSRelational DBMS infocolumn orientedRelational DBMSRelational DBMS
Secondary database modelsGraph DBMS
Search engine
Document store
Spatial DBMS
Document 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
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score8.37
Rank#48  Overall
#30  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Score1.31
Rank#163  Overall
#74  Relational DBMS
Websitewww.gigaspaces.comgreenplum.orgazure.microsoft.com/­services/­data-explorerwww.postgres-xl.orgwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmldocs.greenplum.orgdocs.microsoft.com/­en-us/­azure/­data-explorerwww.postgres-xl.org/­documentationdocs.oracle.com/­database/­timesten-18.1
DeveloperGigaspaces TechnologiesPivotal Software Inc.MicrosoftOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release2000200520192014 infosince 2012, originally named StormDB1998
Current release15.5, September 20207.0.0, September 2023cloud service with continuous releases10 R1, October 201811 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoApache 2.0commercialOpen Source infoMozilla public licensecommercial
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 languageJava, C++, .NetC
Server operating systemsLinux
macOS
Solaris
Windows
LinuxhostedLinux
macOS
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeschema-freeyesFixed schema with schema-less datatypes (dynamic)yesyes
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyes
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.no infoXML can be used for describing objects metadatayes infosince Version 4.2yesyes infoXML type, but no XML query functionalityno
Secondary indexesyesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLSQL-99 for query and DML statementsyesKusto Query Language (KQL), SQL subsetyes infodistributed, parallel query executionyes
APIs and other access methodsGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JDBC
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languages.Net
C++
Java
Python
Scala
C
Java
Perl
Python
R
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresyesyesYes, possible languages: KQL, Python, Ruser defined functionsPL/SQL
Triggersyes, event driven architectureyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud servicehorizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Source-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID infoMVCCACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnononoyes
User concepts infoAccess controlRole-based access controlfine grained access rights according to SQL-standardAzure Active Directory Authenticationfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
GigaSpacesGreenplumMicrosoft Azure Data ExplorerPostgres-XLTimesTen
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