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

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

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonBrytlyt  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonPostgreSQL  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLLarge scale data warehouse service with append-only tablesWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational 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
Score0.38
Rank#279  Overall
#126  Relational DBMS
Score61.90
Rank#19  Overall
#13  Relational DBMS
Score645.05
Rank#4  Overall
#4  Relational DBMS
Websitephoenix.apache.orgbrytlyt.iocloud.google.com/­bigquerywww.postgresql.org
Technical documentationphoenix.apache.orgdocs.brytlyt.iocloud.google.com/­bigquery/­docswww.postgresql.org/­docs
DeveloperApache Software FoundationBrytlytGooglePostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release2014201620101989 info1989: Postgres, 1996: PostgreSQL
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20195.0, August 202316.2, February 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoBSD
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++ and CUDAC
Server operating systemsLinux
Unix
Windows
Linux
OS X
Windows
hostedFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.noyes infospecific XML-type available, but no XML query functionality.
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyesyesyesyes infostandard with numerous extensions
APIs and other access methodsJDBCADO.NET
JDBC
native C library
ODBC
streaming API for large objects
RESTful 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
C
C++
Delphi
Java
Perl
Python
Tcl
.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresuser defined functionsuser defined functions infoin PL/pgSQLuser defined functions infoin JavaScriptuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnonepartitioning by range, list and (since PostgreSQL 11) by hash
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationSource-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 integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno infoSince BigQuery is designed for querying dataACID
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.yesnono
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyfine grained access rights according to SQL-standardAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
Apache PhoenixBrytlytGoogle BigQueryPostgreSQL
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