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DBMS > Apache Impala vs. Firebird vs. FoundationDB vs. Google Cloud Datastore

System Properties Comparison Apache Impala vs. Firebird vs. FoundationDB vs. Google Cloud Datastore

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonFirebird  Xexclude from comparisonFoundationDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparison
Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.
DescriptionAnalytic DBMS for HadoopFirebird is an open source RDBMS forked from Borland's InterBaseOrdered key-value store. Core features are complimented by layers.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform
Primary database modelRelational DBMSRelational DBMSDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Document store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score20.82
Rank#30  Overall
#18  Relational DBMS
Score1.03
Rank#190  Overall
#31  Document stores
#28  Key-value stores
#89  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Websiteimpala.apache.orgwww.firebirdsql.orggithub.com/­apple/­foundationdbcloud.google.com/­datastore
Technical documentationimpala.apache.org/­impala-docs.htmlwww.firebirdsql.org/­en/­reference-manualsapple.github.io/­foundationdbcloud.google.com/­datastore/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaFirebird FoundationFoundationDBGoogle
Initial release20132000 infoAs fork of Borland's InterBase20132008
Current release4.1.0, June 20225.0.0, January 20246.2.28, November 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoInitial Developer's Public LicenseOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C and C++C++
Server operating systemsLinuxAIX
FreeBSD
HP-UX
Linux
OS X
server-less infoFirebird Embedded Server
Solaris
Unix
Windows
Linux
OS X
Windows
hosted
Data schemeyesyesschema-free infosome layers support schemasschema-free
Typing infopredefined data types such as float or dateyesyesno infosome layers support typingyes, details here
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.nono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyessupported in specific SQL layer onlySQL-like query language (GQL)
APIs and other access methodsJDBC
ODBC
ADO.NET
C/C++ API
JDBC infoJaybird
ODBC
OLE DB
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Delphi
Java
JavaScript infoNode.js
Lua
Perl
PHP
Python
Ruby
.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducePSQLin SQL-layer onlyusing Google App Engine
TriggersnoyesnoCallbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationyesMulti-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonoyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyLinearizable consistencyImmediate 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.
Foreign keys infoReferential integritynoyesin SQL-layer onlyyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactions
Concurrency infoSupport for concurrent manipulation of datayesyes infoFeatures a multi-generational MVCC architecture, readers do not block writersyesyes
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.nono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosUsers with fine-grained authorization conceptnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Apache ImpalaFirebirdFoundationDBGoogle Cloud Datastore
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