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DBMS > Badger vs. BigchainDB vs. Google Cloud Spanner vs. HEAVY.AI vs. InterSystems IRIS

System Properties Comparison Badger vs. BigchainDB vs. Google Cloud Spanner vs. HEAVY.AI vs. InterSystems IRIS

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonBigchainDB  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonInterSystems IRIS  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 assetsA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareA containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalability
Primary database modelKey-value storeDocument storeRelational DBMSRelational DBMSDocument store
Key-value store
Object oriented DBMS
Relational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score0.79
Rank#212  Overall
#36  Document stores
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score4.05
Rank#83  Overall
#14  Document stores
#10  Key-value stores
#1  Object oriented DBMS
#45  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerwww.bigchaindb.comcloud.google.com/­spannergithub.com/­heavyai/­heavydb
www.heavy.ai
www.intersystems.com/­products/­intersystems-iris
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerbigchaindb.readthedocs.io/­en/­latestcloud.google.com/­spanner/­docsdocs.heavy.aidocs.intersystems.com/­irislatest/­csp/­docbook/­DocBook.UI.Page.cls
DeveloperDGraph LabsGoogleHEAVY.AI, Inc.InterSystems
Initial release20172016201720162018
Current release5.10, January 20222023.3, June 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoAGPL v3commercialOpen Source infoApache Version 2; enterprise edition availablecommercial
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 CUDA
Server operating systemsBSD
Linux
OS X
Solaris
Windows
LinuxhostedLinuxAIX
Linux
macOS
Ubuntu
Windows
Data schemeschema-freeschema-freeyesyesdepending on used data model
Typing infopredefined data types such as float or datenonoyesyesyes
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.nonononoyes
Secondary indexesnoyesnoyes
SQL infoSupport of SQLnonoyes infoQuery statements complying to ANSI 2011yesyes
APIs and other access methodsCLI Client
RESTful HTTP API
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
JDBC
ODBC
Thrift
Vega
JDBC
ODBC
RESTful HTTP API
Supported programming languagesGoGo
Haskell
Java
JavaScript
Python
Ruby
Go
Java
JavaScript (Node.js)
Python
All languages supporting JDBC/ODBC/Thrift
Python
.Net
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnononoyes
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding infoRound robinSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factorMulti-source replication with 3 replicas for regional instances.Multi-source replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoStrict serializable isolationnoACID
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.nonoyesyes
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-standardyes
More information provided by the system vendor
BadgerBigchainDBGoogle Cloud SpannerHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022InterSystems IRIS
Specific characteristicsInterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
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More resources
BadgerBigchainDBGoogle Cloud SpannerHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022InterSystems IRIS
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