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DBMS > Badger vs. Google Cloud Datastore vs. HEAVY.AI vs. PostgreSQL vs. Spark SQL

System Properties Comparison Badger vs. Google Cloud Datastore vs. HEAVY.AI vs. PostgreSQL vs. Spark SQL

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonPostgreSQL  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeDocument storeRelational DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Relational DBMS
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
Score0.22
Rank#320  Overall
#47  Key-value stores
Score4.36
Rank#72  Overall
#12  Document stores
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score636.25
Rank#4  Overall
#4  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­dgraph-io/­badgercloud.google.com/­datastoregithub.com/­heavyai/­heavydb
www.heavy.ai
www.postgresql.orgspark.apache.org/­sql
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgercloud.google.com/­datastore/­docsdocs.heavy.aiwww.postgresql.org/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDGraph LabsGoogleHEAVY.AI, Inc.PostgreSQL Global Development Group infowww.postgresql.org/­developerApache Software Foundation
Initial release2017200820161989 info1989: Postgres, 1996: PostgreSQL2014
Current release5.10, January 202216.3, May 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache Version 2; enterprise edition availableOpen Source infoBSDOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoC++ and CUDACScala
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hostedLinuxFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeyesyesyes
Typing infopredefined data types such as float or datenoyes, details hereyesyesyes
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.no
Secondary indexesnoyesnoyesno
SQL infoSupport of SQLnoSQL-like query language (GQL)yesyes infostandard with numerous extensionsSQL-like DML and DDL statements
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
Vega
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Supported programming languagesGo.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresnousing Google App Enginenouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.no
TriggersnoCallbacks using the Google Apps Enginenoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoRound robinpartitioning by range, list and (since PostgreSQL 11) by hashyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication using PaxosMulti-source replicationSource-replica replication infoother methods possible by using 3rd party extensionsnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesnono
User concepts infoAccess controlnoAccess 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-standardno

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More resources
BadgerGoogle Cloud DatastoreHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022PostgreSQLSpark SQL
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