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DBMS > Badger vs. BigchainDB vs. Google Cloud Bigtable vs. HEAVY.AI vs. Spark SQL

System Properties Comparison Badger vs. BigchainDB vs. Google Cloud Bigtable vs. HEAVY.AI vs. Spark SQL

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonBigchainDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.BigchainDB is scalable blockchain database offering decentralization, immutability and native assetsGoogle'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 hardwareSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeDocument storeKey-value store
Wide column store
Relational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.25
Rank#315  Overall
#46  Key-value stores
Score0.86
Rank#210  Overall
#36  Document stores
Score3.86
Rank#90  Overall
#13  Key-value stores
#7  Wide column stores
Score2.30
Rank#127  Overall
#60  Relational DBMS
Score19.56
Rank#34  Overall
#21  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerwww.bigchaindb.comcloud.google.com/­bigtablegithub.com/­heavyai/­heavydb
www.heavy.ai
spark.apache.org/­sql
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerbigchaindb.readthedocs.io/­en/­latestcloud.google.com/­bigtable/­docsdocs.heavy.aispark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDGraph LabsGoogleHEAVY.AI, Inc.Apache Software Foundation
Initial release20172016201520162014
Current release5.10, January 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoAGPL v3commercialOpen Source infoApache Version 2; enterprise edition availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoPythonC++ and CUDAScala
Server operating systemsBSD
Linux
OS X
Solaris
Windows
LinuxhostedLinuxLinux
OS X
Windows
Data schemeschema-freeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or datenononoyesyes
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.nonononono
Secondary indexesnononono
SQL infoSupport of SQLnononoyesSQL-like DML and DDL statements
APIs and other access methodsCLI Client
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Thrift
Vega
JDBC
ODBC
Supported programming languagesGoGo
Haskell
Java
JavaScript
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Python
All languages supporting JDBC/ODBC/Thrift
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnononono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding infoRound robinyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factorInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes,with MongoDB ord RethinkDByesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlnoyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardno

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More resources
BadgerBigchainDBGoogle Cloud BigtableHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Spark SQL
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