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DBMS > Apache Phoenix vs. Google BigQuery vs. LMDB vs. PostgreSQL

System Properties Comparison Apache Phoenix vs. Google BigQuery vs. LMDB vs. PostgreSQL

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonLMDB  Xexclude from comparisonPostgreSQL  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseLarge scale data warehouse service with append-only tablesA high performant, light-weight, embedded key-value database libraryWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
Primary database modelRelational DBMSRelational DBMSKey-value storeRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.
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
Score2.02
Rank#130  Overall
#63  Relational DBMS
Score61.90
Rank#19  Overall
#13  Relational DBMS
Score2.33
Rank#118  Overall
#21  Key-value stores
Score645.05
Rank#4  Overall
#4  Relational DBMS
Websitephoenix.apache.orgcloud.google.com/­bigquerywww.symas.com/­symas-embedded-database-lmdbwww.postgresql.org
Technical documentationphoenix.apache.orgcloud.google.com/­bigquery/­docswww.lmdb.tech/­docwww.postgresql.org/­docs
DeveloperApache Software FoundationGoogleSymasPostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release2014201020111989 info1989: Postgres, 1996: PostgreSQL
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20190.9.32, January 202416.2, February 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen SourceOpen Source infoBSD
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCC
Server operating systemsLinux
Unix
Windows
hostedLinux
Unix
Windows
FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes
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.nononoyes infospecific XML-type available, but no XML query functionality.
Secondary indexesyesnonoyes
SQL infoSupport of SQLyesyesnoyes infostandard with numerous extensions
APIs and other access methodsJDBCRESTful HTTP/JSON APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresuser defined functionsuser defined functions infoin JavaScriptnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnonenonepartitioning by range, list and (since PostgreSQL 11) by hash
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
noneSource-replica replication infoother methods possible by using 3rd party extensions
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infoSince BigQuery is designed for querying dataACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesnoyesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)nofine grained access rights according to SQL-standard

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More resources
Apache PhoenixGoogle BigQueryLMDBPostgreSQL
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