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DBMS > Blueflood vs. EDB Postgres vs. GridDB vs. Microsoft Azure Data Explorer vs. SAP SQL Anywhere

System Properties Comparison Blueflood vs. EDB Postgres vs. GridDB vs. Microsoft Azure Data Explorer vs. SAP SQL Anywhere

Editorial information provided by DB-Engines
NameBlueflood  Xexclude from comparisonEDB Postgres  Xexclude from comparisonGridDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSAP SQL Anywhere infoformerly called Adaptive Server Anywhere  Xexclude from comparison
DescriptionScalable TimeSeries DBMS based on CassandraThe EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.Scalable in-memory time series database optimized for IoT and Big DataFully managed big data interactive analytics platformRDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments
Primary database modelTime Series DBMSRelational DBMSTime Series DBMSRelational DBMS infocolumn orientedRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Key-value store
Relational 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.06
Rank#353  Overall
#34  Time Series DBMS
Score1.90
Rank#135  Overall
#63  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score4.25
Rank#79  Overall
#43  Relational DBMS
Websiteblueflood.iowww.enterprisedb.comgriddb.netazure.microsoft.com/­services/­data-explorerwww.sap.com/­products/­technology-platform/­sql-anywhere.html
Technical documentationgithub.com/­rax-maas/­blueflood/­wikiwww.enterprisedb.com/­docsdocs.griddb.netdocs.microsoft.com/­en-us/­azure/­data-explorerhelp.sap.com/­docs/­SAP_SQL_Anywhere
DeveloperRackspaceEnterpriseDBToshiba CorporationMicrosoftSAP infoformerly Sybase
Initial release20132005201320191992
Current release14, December 20215.1, August 2022cloud service with continuous releases17, July 2015
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial infoBSD for PostgreSQL-componentsOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaCC++
Server operating systemsLinux
OS X
Linux
Windows
LinuxhostedAIX
HP-UX
Linux
OS X
Solaris
Windows
Data schemepredefined schemeyesyesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampyes 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.noyes infospecific XML-type available, but no XML query functionality.noyesyes
Secondary indexesnoyesyesall fields are automatically indexedyes
SQL infoSupport of SQLnoyes infostandard with numerous extensionsSQL92, SQL-like TQL (Toshiba Query Language)Kusto Query Language (KQL), SQL subsetyes
APIs and other access methodsHTTP RESTADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
HTTP API
JDBC
ODBC
Supported programming languages.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.noYes, possible languages: KQL, Python, Ryes, in C/C++, Java, .Net or Perl
Triggersnoyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on Cassandrahorizontal partitioning infoby hash, list or rangeShardingSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on CassandraMulti-source replicationSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication infoDatabase mirroring
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyImmediate consistency within container, eventual consistency across containersEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID at container levelnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyesyes
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.nonoyesnoyes
User concepts infoAccess controlnofine grained access rights according to SQL-standardAccess rights for users can be defined per databaseAzure Active Directory Authenticationfine grained access rights according to SQL-standard
More information provided by the system vendor
BluefloodEDB PostgresGridDBMicrosoft Azure Data ExplorerSAP SQL Anywhere infoformerly called Adaptive Server Anywhere
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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BluefloodEDB PostgresGridDBMicrosoft Azure Data ExplorerSAP SQL Anywhere infoformerly called Adaptive Server Anywhere
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