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DBMS > Brytlyt vs. Google Cloud Bigtable vs. Linter vs. PostgreSQL

System Properties Comparison Brytlyt vs. Google Cloud Bigtable vs. Linter vs. PostgreSQL

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Editorial information provided by DB-Engines
NameBrytlyt  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonLinter  Xexclude from comparisonPostgreSQL  Xexclude from comparison
DescriptionScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.RDBMS for high security requirementsWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
Primary database modelRelational DBMSKey-value store
Wide column store
Relational DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.
Secondary database modelsSpatial DBMSDocument 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
Score0.29
Rank#288  Overall
#131  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.09
Rank#346  Overall
#152  Relational DBMS
Score645.54
Rank#4  Overall
#4  Relational DBMS
Websitebrytlyt.iocloud.google.com/­bigtablelinter.ruwww.postgresql.org
Technical documentationdocs.brytlyt.iocloud.google.com/­bigtable/­docswww.postgresql.org/­docs
DeveloperBrytlytGooglerelex.ruPostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release2016201519901989 info1989: Postgres, 1996: PostgreSQL
Current release5.0, August 202316.3, May 2024
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoBSD
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++ and CUDAC and C++C
Server operating systemsLinux
OS X
Windows
hostedAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyes
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.yes infospecific XML-type available, but no XML query functionality.nonoyes infospecific XML-type available, but no XML query functionality.
Secondary indexesyesnoyesyes
SQL infoSupport of SQLyesnoyesyes infostandard with numerous extensions
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
C
C++
Delphi
Java
Perl
Python
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresuser defined functions infoin PL/pgSQLnoyes infoproprietary syntax with the possibility to convert from PL/SQLuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
Triggersyesnoyesyes
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 nodesSource-replica replicationInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationSource-replica replication infoother methods possible by using 3rd party extensions
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACIDACID
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.nono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
BrytlytGoogle Cloud BigtableLinterPostgreSQL
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1 August 2023, PR Newswire

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