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DBMS > Badger vs. BigchainDB vs. HEAVY.AI vs. IBM Db2 Event Store vs. TypeDB

System Properties Comparison Badger vs. BigchainDB vs. HEAVY.AI vs. IBM Db2 Event Store vs. TypeDB

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonBigchainDB  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonTypeDB infoformerly named Grakn  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 high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareDistributed Event Store optimized for Internet of Things use casesTypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language
Primary database modelKey-value storeDocument storeRelational DBMSEvent Store
Time Series DBMS
Graph DBMS
Relational DBMS infoOften described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.
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
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score0.65
Rank#234  Overall
#20  Graph DBMS
#107  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerwww.bigchaindb.comgithub.com/­heavyai/­heavydb
www.heavy.ai
www.ibm.com/­products/­db2-event-storetypedb.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerbigchaindb.readthedocs.io/­en/­latestdocs.heavy.aiwww.ibm.com/­docs/­en/­db2-event-storetypedb.com/­docs
DeveloperDGraph LabsHEAVY.AI, Inc.IBMVaticle
Initial release20172016201620172016
Current release5.10, January 20222.02.26.3, January 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoAGPL v3Open Source infoApache Version 2; enterprise edition availablecommercial infofree developer edition availableOpen Source infoGPL Version 3, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoPythonC++ and CUDAC and C++Java
Server operating systemsBSD
Linux
OS X
Solaris
Windows
LinuxLinuxLinux infoLinux, macOS, Windows for the developer additionLinux
OS X
Windows
Data schemeschema-freeschema-freeyesyesyes
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.nonononono
Secondary indexesnononoyes
SQL infoSupport of SQLnonoyesyes infothrough the embedded Spark runtimeno
APIs and other access methodsCLI Client
RESTful HTTP API
JDBC
ODBC
Thrift
Vega
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)
Supported programming languagesGoGo
Haskell
Java
JavaScript
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresnonoyesno
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoRound robinShardingSharding infoby using Cassandra
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factorMulti-source replicationActive-active shard replicationMulti-source replication infoby using Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononoyes infoby using Apache Kafka and Apache Zookeeper
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononono infosubstituted by the relationship feature
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesNo - written data is immutableyes
Durability infoSupport for making data persistentyesyes,with MongoDB ord RethinkDByesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesno
User concepts infoAccess controlnoyesfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardyes infoat REST API level; other APIs in progress
More information provided by the system vendor
BadgerBigchainDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022IBM Db2 Event StoreTypeDB infoformerly named Grakn
Specific characteristicsTypeDB is a polymorphic database with a conceptual data model, a strong subtyping...
» more
Competitive advantagesTypeDB provides a new level of expressivity, extensibility, interoperability, and...
» more
Typical application scenariosLife sciences : TypeDB makes working with biological data much easier and accelerates...
» more
Licensing and pricing modelsApache f or language drivers, and AGPL and Commercial for the database server. The...
» more

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More resources
BadgerBigchainDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022IBM Db2 Event StoreTypeDB infoformerly named Grakn
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