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DBMS > GBase vs. GridDB vs. HEAVY.AI vs. Microsoft Azure Data Explorer vs. Sqrrl

System Properties Comparison GBase vs. GridDB vs. HEAVY.AI vs. Microsoft Azure Data Explorer vs. Sqrrl

Editorial information provided by DB-Engines
NameGBase  Xexclude from comparisonGridDB  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionAn analytical database for business intelligence with large customers in China.Scalable in-memory time series database optimized for IoT and Big DataA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareFully managed big data interactive analytics platformAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelRelational DBMSTime Series DBMSRelational DBMSRelational DBMS infocolumn orientedDocument store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsKey-value store
Relational DBMS
Spatial DBMSDocument 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
Score1.04
Rank#190  Overall
#88  Relational DBMS
Score2.02
Rank#132  Overall
#11  Time Series DBMS
Score2.10
Rank#126  Overall
#61  Relational DBMS
Score5.16
Rank#69  Overall
#37  Relational DBMS
Websitewww.gbase.cngriddb.netgithub.com/­heavyai/­heavydb
www.heavy.ai
azure.microsoft.com/­services/­data-explorersqrrl.com
Technical documentationdocs.griddb.netdocs.heavy.aidocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperToshiba CorporationHEAVY.AI, Inc.MicrosoftAmazon infooriginally Sqrrl Data, Inc.
Initial release2013201620192012
Current releaseGBase 8a5.1, August 20225.10, January 2022cloud service with continuous releases
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache Version 2; enterprise edition 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 languageC++C++ and CUDAJava
Server operating systemsLinuxLinuxhostedLinux
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesyes 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.nonoyes
Secondary indexesyesnoall fields are automatically indexedyes
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)yesKusto Query Language (KQL), SQL subsetno
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
Vega
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresnonoYes, possible languages: KQL, Python, Rno
Triggersyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoRound robinSharding infoImplicit feature of the cloud serviceSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelnonoAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlAccess rights for users can be defined per databasefine grained access rights according to SQL-standardAzure Active Directory AuthenticationCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)
More information provided by the system vendor
GBaseGridDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Microsoft Azure Data ExplorerSqrrl
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
GBaseGridDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Microsoft Azure Data ExplorerSqrrl
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