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DBMS > Badger vs. BigchainDB vs. Google Cloud Datastore vs. HEAVY.AI vs. Microsoft Azure Table Storage

System Properties Comparison Badger vs. BigchainDB vs. Google Cloud Datastore vs. HEAVY.AI vs. Microsoft Azure Table Storage

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonBigchainDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonMicrosoft Azure Table Storage  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 assetsAutomatically 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 hardwareA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelKey-value storeDocument storeDocument storeRelational DBMSWide column store
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
Score4.47
Rank#76  Overall
#12  Document stores
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Websitegithub.com/­dgraph-io/­badgerwww.bigchaindb.comcloud.google.com/­datastoregithub.com/­heavyai/­heavydb
www.heavy.ai
azure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerbigchaindb.readthedocs.io/­en/­latestcloud.google.com/­datastore/­docsdocs.heavy.ai
DeveloperDGraph LabsGoogleHEAVY.AI, Inc.Microsoft
Initial release20172016200820162012
Current release5.10, January 2022
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 servicenonoyesnoyes
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
LinuxhostedLinuxhosted
Data schemeschema-freeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or datenonoyes, details hereyesyes
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 indexesnoyesnono
SQL infoSupport of SQLnonoSQL-like query language (GQL)yesno
APIs and other access methodsCLI Client
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
Vega
RESTful HTTP API
Supported programming languagesGoGo
Haskell
Java
JavaScript
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnousing Google App Enginenono
TriggersnoCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding infoRound robinSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factorMulti-source replication using PaxosMulti-source replicationyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes 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 integritynonoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnooptimistic locking
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-standardAccess rights based on private key authentication or shared access signatures

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More resources
BadgerBigchainDBGoogle Cloud DatastoreHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Microsoft Azure Table Storage
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