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DBMS > Badger vs. Google Cloud Bigtable vs. RethinkDB vs. Tigris

System Properties Comparison Badger vs. Google Cloud Bigtable vs. RethinkDB vs. Tigris

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonRethinkDB  Xexclude from comparisonTigris  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.DBMS for the Web with a mechanism to push updated query results to applications in realtime.A horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure
Primary database modelKey-value storeKey-value store
Wide column store
Document storeDocument store
Key-value store
Search engine
Time Series DBMS
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
Score2.66
Rank#107  Overall
#20  Document stores
Score0.09
Rank#363  Overall
#49  Document stores
#54  Key-value stores
#22  Search engines
#38  Time Series DBMS
Websitegithub.com/­dgraph-io/­badgercloud.google.com/­bigtablerethinkdb.comwww.tigrisdata.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgercloud.google.com/­bigtable/­docsrethinkdb.com/­docswww.tigrisdata.com/­docs
DeveloperDGraph LabsGoogleThe Linux Foundation infosince July 2017Tigris Data, Inc.
Initial release2017201520092022
Current release2.4.1, August 2020
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache Version 2Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoC++
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hostedLinux
OS X
Windows
Linux
macOS
Windows
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or datenonoyes infostring, binary, float, bool, date, geometryyes
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.nononono
Secondary indexesnonoyesyes
SQL infoSupport of SQLnononono
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
CLI Client
gRPC
RESTful HTTP API
Supported programming languagesGoC#
C++
Go
Java
JavaScript (Node.js)
Python
C infocommunity-supported driver
C# infocommunity-supported driver
C++ infocommunity-supported driver
Clojure infocommunity-supported driver
Dart infocommunity-supported driver
Erlang infocommunity-supported driver
Go infocommunity-supported driver
Haskell infocommunity-supported driver
Java infoofficial driver
JavaScript (Node.js) infoofficial driver
Lisp infocommunity-supported driver
Lua infocommunity-supported driver
Objective-C infocommunity-supported driver
Perl infocommunity-supported driver
PHP infocommunity-supported driver
Python infoofficial driver
Ruby infoofficial driver
Scala infocommunity-supported driver
Go
Java
JavaScript (Node.js)
Server-side scripts infoStored proceduresnonono
TriggersnonoClient-side triggers through changefeedsno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding inforange basedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes
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 integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsAtomic single-document operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCC basedyes
Durability infoSupport for making data persistentyesyesyesyes, using FoundationDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes infousers and table-level permissionsAccess rights for users and roles

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More resources
BadgerGoogle Cloud BigtableRethinkDBTigris
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