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DBMS > Google Cloud Bigtable vs. HEAVY.AI vs. LevelDB vs. PostgreSQL

System Properties Comparison Google Cloud Bigtable vs. HEAVY.AI vs. LevelDB vs. PostgreSQL

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonLevelDB  Xexclude from comparisonPostgreSQL  Xexclude from comparison
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
Primary database modelKey-value store
Wide column store
Relational 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 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
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score2.35
Rank#111  Overall
#19  Key-value stores
Score645.54
Rank#4  Overall
#4  Relational DBMS
Websitecloud.google.com/­bigtablegithub.com/­heavyai/­heavydb
www.heavy.ai
github.com/­google/­leveldbwww.postgresql.org
Technical documentationcloud.google.com/­bigtable/­docsdocs.heavy.aigithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdwww.postgresql.org/­docs
DeveloperGoogleHEAVY.AI, Inc.GooglePostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release2015201620111989 info1989: Postgres, 1996: PostgreSQL
Current release5.10, January 20221.23, February 202116.2, February 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; enterprise edition availableOpen Source infoBSDOpen Source infoBSD
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Aiven for PostgreSQL: Fully managed PostgreSQL for developers with 70+ extensions and flexible orchestration tools.
Implementation languageC++ and CUDAC++C
Server operating systemshostedLinuxIllumos
Linux
OS X
Windows
FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or datenoyesnoyes
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 indexesnononoyes
SQL infoSupport of SQLnoyesnoyes infostandard with numerous extensions
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Thrift
Vega
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
All languages supporting JDBC/ODBC/Thrift
Python
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresnononouser 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 nodesShardingSharding infoRound robinnonepartitioning by range, list and (since PostgreSQL 11) by hash
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replicationnoneSource-replica replication infoother methods possible by using 3rd party extensions
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infowith automatic compression on writesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard

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More resources
Google Cloud BigtableHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022LevelDBPostgreSQL
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