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DBMS > Google BigQuery vs. PostgreSQL vs. Prometheus vs. Sphinx vs. Splice Machine

System Properties Comparison Google BigQuery vs. PostgreSQL vs. Prometheus vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonPostgreSQL  Xexclude from comparisonPrometheus  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionLarge scale data warehouse service with append-only tablesWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLOpen-source Time Series DBMS and monitoring systemOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Time Series DBMSSearch engineRelational DBMS
Secondary database modelsDocument store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score60.38
Rank#19  Overall
#13  Relational DBMS
Score645.54
Rank#4  Overall
#4  Relational DBMS
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitecloud.google.com/­bigquerywww.postgresql.orgprometheus.iosphinxsearch.comsplicemachine.com
Technical documentationcloud.google.com/­bigquery/­docswww.postgresql.org/­docsprometheus.io/­docssphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperGooglePostgreSQL Global Development Group infowww.postgresql.org/­developerSphinx Technologies Inc.Splice Machine
Initial release20101989 info1989: Postgres, 1996: PostgreSQL201520012014
Current release16.3, May 20243.5.1, February 20233.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoBSDOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCGoC++Java
Server operating systemshostedFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Linux
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesNumeric data onlynoyes
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 infospecific XML-type available, but no XML query functionality.no infoImport of XML data possible
Secondary indexesnoyesnoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLyesyes infostandard with numerous extensionsnoSQL-like query language (SphinxQL)yes
APIs and other access methodsRESTful HTTP/JSON APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
RESTful HTTP/JSON APIProprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.nonoyes infoJava
Triggersnoyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesnonepartitioning by range, list and (since PostgreSQL 11) by hashShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsyes infoby FederationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencynoneImmediate Consistency
Foreign keys infoReferential integritynoyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoSince BigQuery is designed for querying dataACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)fine grained access rights according to SQL-standardnonoAccess rights for users, groups and roles according to SQL-standard

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More resources
Google BigQueryPostgreSQLPrometheusSphinxSplice Machine
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