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DBMS > DolphinDB vs. GridDB vs. Interbase vs. Microsoft Azure Data Explorer vs. Sqrrl

System Properties Comparison DolphinDB vs. GridDB vs. Interbase vs. Microsoft Azure Data Explorer vs. Sqrrl

Editorial information provided by DB-Engines
NameDolphinDB  Xexclude from comparisonGridDB  Xexclude from comparisonInterbase  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.
DescriptionDolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.Scalable in-memory time series database optimized for IoT and Big DataLight-weight proven RDBMS infooriginally from BorlandFully managed big data interactive analytics platformAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelTime Series DBMSTime Series DBMSRelational DBMSRelational DBMS infocolumn orientedDocument store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsRelational DBMSKey-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
Score4.03
Rank#78  Overall
#6  Time Series DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score4.08
Rank#75  Overall
#41  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websitewww.dolphindb.comgriddb.netwww.embarcadero.com/­products/­interbaseazure.microsoft.com/­services/­data-explorersqrrl.com
Technical documentationdocs.dolphindb.cn/­en/­help200/­index.htmldocs.griddb.netdocs.embarcadero.com/­products/­interbasedocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperDolphinDB, IncToshiba CorporationEmbarcaderoMicrosoftAmazon infooriginally Sqrrl Data, Inc.
Initial release20182013198420192012
Current releasev2.00.4, January 20225.1, August 2022InterBase 2020, December 2019cloud service with continuous releases
License infoCommercial or Open Sourcecommercial infofree community version availableOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialcommercialcommercial
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++CJava
Server operating systemsLinux
Windows
LinuxAndroid
iOS
Linux
OS X
Windows
hostedLinux
Data schemeyesyesyesFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateyesyes 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.nonono infoexport as XML data possibleyes
Secondary indexesyesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLSQL-like query languageSQL92, SQL-like TQL (Toshiba Query Language)yesKusto Query Language (KQL), SQL subsetno
APIs and other access methodsJDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
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
MatLab
Python
R
Rust
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby
.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 proceduresyesnoyes infoInterbase procedure and trigger languageYes, possible languages: KQL, Python, Rno
Triggersnoyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingnoneSharding infoImplicit feature of the cloud serviceSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationInterbase Change Viewsyes 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 methodsyesConnector 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 ConsistencyImmediate 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 integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACID at container levelACIDnoAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMultiversion concurreny controlyesyes
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.yesyesyesno
User concepts infoAccess controlAdministrators, Users, GroupsAccess 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
DolphinDBGridDBInterbaseMicrosoft 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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DolphinDBGridDBInterbaseMicrosoft Azure Data ExplorerSqrrl
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