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DBMS > AnzoGraph DB vs. Badger vs. BigchainDB vs. HEAVY.AI vs. Microsoft Azure Table Storage

System Properties Comparison AnzoGraph DB vs. Badger vs. BigchainDB vs. HEAVY.AI vs. Microsoft Azure Table Storage

Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonBadger  Xexclude from comparisonBigchainDB  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.BigchainDB is scalable blockchain database offering decentralization, immutability and native assetsA 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 modelGraph DBMS
RDF store
Key-value storeDocument storeRelational DBMSWide column store
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#307  Overall
#24  Graph DBMS
#13  RDF stores
Score0.14
Rank#331  Overall
#49  Key-value stores
Score0.79
Rank#212  Overall
#36  Document stores
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Websitecambridgesemantics.com/­anzographgithub.com/­dgraph-io/­badgerwww.bigchaindb.comgithub.com/­heavyai/­heavydb
www.heavy.ai
azure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmgodoc.org/­github.com/­dgraph-io/­badgerbigchaindb.readthedocs.io/­en/­latestdocs.heavy.ai
DeveloperCambridge SemanticsDGraph LabsHEAVY.AI, Inc.Microsoft
Initial release20182017201620162012
Current release2.3, January 20215.10, January 2022
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoApache 2.0Open Source infoAGPL v3Open Source infoApache Version 2; enterprise edition availablecommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoPythonC++ and CUDA
Server operating systemsLinuxBSD
Linux
OS X
Solaris
Windows
LinuxLinuxhosted
Data schemeSchema-free and OWL/RDFS-schema supportschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or datenonoyesyes
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 SQLSPARQL and SPARQL* as primary query language. Cypher preview.nonoyesno
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
CLI Client
RESTful HTTP API
JDBC
ODBC
Thrift
Vega
RESTful HTTP API
Supported programming languagesC++
Java
Python
GoGo
Haskell
Java
JavaScript
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesnonono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingnoneShardingSharding infoRound robinSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-Clusternoneselectable replication factorMulti-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 methodsKerberos/HDFS data loadingnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusternoneImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infonot needed in graphsnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes,with MongoDB ord RethinkDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesno
User concepts infoAccess controlAccess rights for users and rolesnoyesfine grained access rights according to SQL-standardAccess rights based on private key authentication or shared access signatures

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More resources
AnzoGraph DBBadgerBigchainDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Microsoft Azure Table Storage
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