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

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

Editorial information provided by DB-Engines
NameBlueflood  Xexclude from comparisonGridDB  Xexclude from comparisonHypertable  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSAP SQL Anywhere infoformerly called Adaptive Server Anywhere  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionScalable TimeSeries DBMS based on CassandraScalable in-memory time series database optimized for IoT and Big DataAn open source BigTable implementation based on distributed file systems such as HadoopFully managed big data interactive analytics platformRDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments
Primary database modelTime Series DBMSTime Series DBMSWide column storeRelational DBMS infocolumn orientedRelational DBMS
Secondary database modelsKey-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
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score4.25
Rank#79  Overall
#43  Relational DBMS
Websiteblueflood.iogriddb.netazure.microsoft.com/­services/­data-explorerwww.sap.com/­products/­technology-platform/­sql-anywhere.html
Technical documentationgithub.com/­rax-maas/­blueflood/­wikidocs.griddb.netdocs.microsoft.com/­en-us/­azure/­data-explorerhelp.sap.com/­docs/­SAP_SQL_Anywhere
DeveloperRackspaceToshiba CorporationHypertable Inc.MicrosoftSAP infoformerly Sybase
Initial release20132013200920191992
Current release5.1, August 20220.9.8.11, March 2016cloud service with continuous releases17, July 2015
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoGNU version 3. Commercial license 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 languageJavaC++C++
Server operating systemsLinux
OS X
LinuxLinux
OS X
Windows infoan inofficial Windows port is available
hostedAIX
HP-UX
Linux
OS X
Solaris
Windows
Data schemepredefined schemeyesschema-freeFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampnoyes 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.nonoyesyes
Secondary indexesnoyesrestricted infoonly exact value or prefix value scansall fields are automatically indexedyes
SQL infoSupport of SQLnoSQL92, SQL-like TQL (Toshiba Query Language)noKusto Query Language (KQL), SQL subsetyes
APIs and other access methodsHTTP RESTJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
C++ API
Thrift
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
HTTP API
JDBC
ODBC
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++
Java
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 proceduresnononoYes, possible languages: KQL, Python, Ryes, in C/C++, Java, .Net or Perl
Triggersnoyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraShardingShardingSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on CassandraSource-replica replicationselectable replication factor on file system levelyes 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 methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyesSpark 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 consistency within container, eventual consistency across containersImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at container levelnonoACID
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.noyesnoyes
User concepts infoAccess controlnoAccess rights for users can be defined per databasenoAzure Active Directory Authenticationfine grained access rights according to SQL-standard
More information provided by the system vendor
BluefloodGridDBHypertableMicrosoft 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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More resources
BluefloodGridDBHypertableMicrosoft Azure Data ExplorerSAP SQL Anywhere infoformerly called Adaptive Server Anywhere
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