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DBMS > Drizzle vs. Firebird vs. Google Cloud Datastore vs. searchxml vs. Spark SQL

System Properties Comparison Drizzle vs. Firebird vs. Google Cloud Datastore vs. searchxml vs. Spark SQL

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonFirebird  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonsearchxml  Xexclude from comparisonSpark SQL  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Firebird is an open source RDBMS forked from Borland's InterBaseAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDBMS for structured and unstructured content wrapped with an application serverSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSDocument storeNative XML DBMS
Search engine
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score20.50
Rank#30  Overall
#18  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score0.03
Rank#390  Overall
#7  Native XML DBMS
#24  Search engines
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.firebirdsql.orgcloud.google.com/­datastorewww.searchxml.net/­category/­productsspark.apache.org/­sql
Technical documentationwww.firebirdsql.org/­en/­reference-manualscloud.google.com/­datastore/­docswww.searchxml.net/­support/­handoutsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDrizzle project, originally started by Brian AkerFirebird FoundationGoogleinformationpartners gmbhApache Software Foundation
Initial release20082000 infoAs fork of Borland's InterBase200820152014
Current release7.2.4, September 20125.0.0, January 20241.03.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoGNU GPLOpen Source infoInitial Developer's Public LicensecommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C and C++C++Scala
Server operating systemsFreeBSD
Linux
OS X
AIX
FreeBSD
HP-UX
Linux
OS X
server-less infoFirebird Embedded Server
Solaris
Unix
Windows
hostedWindowsLinux
OS X
Windows
Data schemeyesyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes, details hereyesyes
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.noyesno
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLyes infowith proprietary extensionsyesSQL-like query language (GQL)noSQL-like DML and DDL statements
APIs and other access methodsJDBCADO.NET
C/C++ API
JDBC infoJaybird
ODBC
OLE DB
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP API
WebDAV
XQuery
XSLT
JDBC
ODBC
Supported programming languagesC
C++
Java
PHP
C
C#
C++
Delphi
Java
JavaScript infoNode.js
Lua
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++ infomost other programming languages supported via APIsJava
Python
R
Scala
Server-side scripts infoStored proceduresnoPSQLusing Google App Engineyes infoon the application serverno
Triggersno infohooks for callbacks inside the server can be used.yesCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationMulti-source replication using Paxosyes infosychronisation to multiple collectionsnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowno
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 Consistency
Foreign keys infoReferential integrityyesyesyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsmultiple readers, single writerno
Concurrency infoSupport for concurrent manipulation of datayesyes infoFeatures a multi-generational MVCC architecture, readers do not block writersyesyesyes
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.nonono
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPUsers with fine-grained authorization conceptAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Domain, group and role-based access control at the document level and for application servicesno

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More resources
DrizzleFirebirdGoogle Cloud DatastoresearchxmlSpark SQL
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