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DBMS > Badger vs. Brytlyt vs. Google Cloud Bigtable vs. Riak TS

System Properties Comparison Badger vs. Brytlyt vs. Google Cloud Bigtable vs. Riak TS

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonBrytlyt  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonRiak TS  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV
Primary database modelKey-value storeRelational DBMSKey-value store
Wide column store
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#328  Overall
#48  Key-value stores
Score0.27
Rank#292  Overall
#132  Relational DBMS
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Score0.17
Rank#318  Overall
#27  Time Series DBMS
Websitegithub.com/­dgraph-io/­badgerbrytlyt.iocloud.google.com/­bigtable
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.brytlyt.iocloud.google.com/­bigtable/­docswww.tiot.jp/­riak-docs/­riak/­ts/­latest
DeveloperDGraph LabsBrytlytGoogleOpen Source, formerly Basho Technologies
Initial release2017201620152015
Current release5.0, August 20233.0.0, September 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialOpen Source
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoC, C++ and CUDAErlang
Server operating systemsBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
hostedLinux
OS X
Data schemeschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or datenoyesnono
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.noyes infospecific XML-type available, but no XML query functionality.nono
Secondary indexesnoyesnorestricted
SQL infoSupport of SQLnoyesnoyes, limited
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP API
Native Erlang Interface
Supported programming languagesGo.Net
C
C++
Delphi
Java
Perl
Python
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Python
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresnouser defined functions infoin PL/pgSQLnoErlang
Triggersnoyesnoyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationInternal replication in Colossus, and regional replication between two clusters in different zonesselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Foreign keys infoReferential integritynoyesnono infolinks between datasets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDAtomic single-row operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlnofine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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More resources
BadgerBrytlytGoogle Cloud BigtableRiak TS
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