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DBMS > Firebird vs. GridDB vs. MarkLogic vs. Microsoft Azure Data Explorer vs. TimescaleDB

System Properties Comparison Firebird vs. GridDB vs. MarkLogic vs. Microsoft Azure Data Explorer vs. TimescaleDB

Editorial information provided by DB-Engines
NameFirebird  Xexclude from comparisonGridDB  Xexclude from comparisonMarkLogic  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionFirebird is an open source RDBMS forked from Borland's InterBaseScalable in-memory time series database optimized for IoT and Big DataOperational and transactional Enterprise NoSQL databaseFully managed big data interactive analytics platformA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSTime Series DBMSDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMS infocolumn orientedTime Series 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
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score20.82
Rank#30  Overall
#18  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitewww.firebirdsql.orggriddb.netwww.marklogic.comazure.microsoft.com/­services/­data-explorerwww.timescale.com
Technical documentationwww.firebirdsql.org/­en/­reference-manualsdocs.griddb.netdocs.marklogic.comdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.timescale.com
DeveloperFirebird FoundationToshiba CorporationMarkLogic Corp.MicrosoftTimescale
Initial release2000 infoAs fork of Borland's InterBase2013200120192017
Current release5.0.0, January 20245.1, August 202211.0, December 2022cloud service with continuous releases2.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoInitial Developer's Public LicenseOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial inforestricted free version is availablecommercialOpen Source infoApache 2.0
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 and C++C++C++C
Server operating systemsAIX
FreeBSD
HP-UX
Linux
OS X
server-less infoFirebird Embedded Server
Solaris
Unix
Windows
LinuxLinux
OS X
Windows
hostedLinux
OS X
Windows
Data schemeyesyesschema-free infoSchema can be enforcedFixed schema with schema-less datatypes (dynamic)yes
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-typesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.noyesyesyes
Secondary indexesyesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLyesSQL92, SQL-like TQL (Toshiba Query Language)yes infoSQL92Kusto Query Language (KQL), SQL subsetyes infofull PostgreSQL SQL syntax
APIs and other access methodsADO.NET
C/C++ API
JDBC infoJaybird
ODBC
OLE DB
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Delphi
Java
JavaScript infoNode.js
Lua
Perl
PHP
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresPSQLnoyes infovia XQuery or JavaScriptYes, possible languages: KQL, Python, Ruser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyesyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding infoImplicit feature of the cloud serviceyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelACID infocan act as a resource manager in an XA/JTA transactionnoACID
Concurrency infoSupport for concurrent manipulation of datayes infoFeatures a multi-generational MVCC architecture, readers do not block writersyesyesyesyes
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.yesyes, with Range Indexesnono
User concepts infoAccess controlUsers with fine-grained authorization conceptAccess rights for users can be defined per databaseRole-based access control at the document and subdocument levelsAzure Active Directory Authenticationfine grained access rights according to SQL-standard
More information provided by the system vendor
FirebirdGridDBMarkLogicMicrosoft Azure Data ExplorerTimescaleDB
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
FirebirdGridDBMarkLogicMicrosoft Azure Data ExplorerTimescaleDB
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