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DBMS > Badger vs. Google Cloud Bigtable vs. HEAVY.AI vs. Memgraph vs. TerarkDB

System Properties Comparison Badger vs. Google Cloud Bigtable vs. HEAVY.AI vs. Memgraph vs. TerarkDB

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonMemgraph  Xexclude from comparisonTerarkDB  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Google'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 hardwareAn open source graph database built for real-time streaming and compatible with Neo4jA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelKey-value storeKey-value store
Wide column store
Relational DBMSGraph DBMSKey-value store
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#320  Overall
#47  Key-value stores
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score3.19
Rank#94  Overall
#8  Graph DBMS
Score0.08
Rank#367  Overall
#56  Key-value stores
Websitegithub.com/­dgraph-io/­badgercloud.google.com/­bigtablegithub.com/­heavyai/­heavydb
www.heavy.ai
memgraph.comgithub.com/­bytedance/­terarkdb
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgercloud.google.com/­bigtable/­docsdocs.heavy.aimemgraph.com/­docsbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
Social network pagesLinkedInTwitterFacebookGitHubDiscord
DeveloperDGraph LabsGoogleHEAVY.AI, Inc.Memgraph LtdByteDance, originally Terark
Initial release20172015201620172016
Current release5.10, January 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache Version 2; enterprise edition availableOpen Source infoBSL 1.1; commercial license for enterprise edition availablecommercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++ and CUDAC and C++C++
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hostedLinuxLinux
Data schemeschema-freeschema-freeyesschema-free and schema-optionalschema-free
Typing infopredefined data types such as float or datenonoyesyesno
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 SQLnonoyesnono
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Thrift
Vega
Bolt protocol
Cypher query language
C++ API
Java API
Supported programming languagesGoC#
C++
Go
Java
JavaScript (Node.js)
Python
All languages supporting JDBC/ODBC/Thrift
Python
.Net
C
C++
Elixir
Go
Haskell
Java
JavaScript
PHP
Python
Ruby
Scala
C++
Java
Server-side scripts infoStored proceduresnononono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoRound robinSharding infodynamic graph partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replicationMulti-source replication using RAFTnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes inforelationships in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsnoACID infowith snapshot isolationno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyes infowith periodic snapshot and write-ahead logging (WAL) of changesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyesyes
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardUsers, roles and permissionsno
More information provided by the system vendor
BadgerGoogle Cloud BigtableHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022MemgraphTerarkDB
Specific characteristicsMemgraph directly connects to your streaming infrastructure so you and your team...
» more
Competitive advantagesBusiness Source License ensures a future for the Memgraph community MAGE algorithm...
» more
Typical application scenariosGraph algorithms in bioinformatics Social network analysis Cryptocurrency network...
» more
Licensing and pricing modelsYou can check out our pricing model and licenses on the company website .
» more

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More resources
BadgerGoogle Cloud BigtableHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022MemgraphTerarkDB
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