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DBMS > Firebird vs. Google Cloud Datastore vs. TimescaleDB vs. Vitess

System Properties Comparison Firebird vs. Google Cloud Datastore vs. TimescaleDB vs. Vitess

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Editorial information provided by DB-Engines
NameFirebird  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonTimescaleDB  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionFirebird is an open source RDBMS forked from Borland's InterBaseAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMSDocument storeTime Series DBMSRelational DBMS
Secondary database modelsRelational DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score20.82
Rank#30  Overall
#18  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitewww.firebirdsql.orgcloud.google.com/­datastorewww.timescale.comvitess.io
Technical documentationwww.firebirdsql.org/­en/­reference-manualscloud.google.com/­datastore/­docsdocs.timescale.comvitess.io/­docs
DeveloperFirebird FoundationGoogleTimescaleThe Linux Foundation, PlanetScale
Initial release2000 infoAs fork of Borland's InterBase200820172013
Current release5.0.0, January 20242.13.0, November 202315.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoInitial Developer's Public LicensecommercialOpen Source infoApache 2.0Open Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++CGo
Server operating systemsAIX
FreeBSD
HP-UX
Linux
OS X
server-less infoFirebird Embedded Server
Solaris
Unix
Windows
hostedLinux
OS X
Windows
Docker
Linux
macOS
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes, details herenumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex 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
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesSQL-like query language (GQL)yes infofull PostgreSQL SQL syntaxyes infowith proprietary extensions
APIs and other access methodsADO.NET
C/C++ API
JDBC infoJaybird
ODBC
OLE DB
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC
C#
C++
Delphi
Java
JavaScript infoNode.js
Lua
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresPSQLusing Google App Engineuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellyes infoproprietary syntax
TriggersyesCallbacks using the Google Apps Engineyesyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes, across time and space (hash partitioning) attributesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication using PaxosSource-replica replication with hot standby and reads on replicas infoMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsyesyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayes infoFeatures a multi-generational MVCC architecture, readers do not block writersyesyesyes infotable locks or row locks depending on storage engine
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.nonoyes
User concepts infoAccess controlUsers with fine-grained authorization conceptAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardUsers with fine-grained authorization concept infono user groups or roles

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More resources
FirebirdGoogle Cloud DatastoreTimescaleDBVitess
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