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DBMS > Badger vs. Google Cloud Bigtable vs. SingleStore

System Properties Comparison Badger vs. Google Cloud Bigtable vs. SingleStore

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonSingleStore infoformer name was MemSQL  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.MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type
Primary database modelKey-value storeKey-value store
Wide column store
Relational DBMS
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#321  Overall
#47  Key-value stores
Score2.70
Rank#96  Overall
#15  Key-value stores
#7  Wide column stores
Score4.19
Rank#66  Overall
#36  Relational DBMS
Websitegithub.com/­dgraph-io/­badgercloud.google.com/­bigtablewww.singlestore.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgercloud.google.com/­bigtable/­docsdocs.singlestore.com
DeveloperDGraph LabsGoogleSingleStore Inc.
Initial release201720152013
Current release8.5, January 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercial infofree developer edition available
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++, Go
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hostedLinux info64 bit version required
Data schemeschema-freeschema-freeyes
Typing infopredefined data types such as float or datenonoyes
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.nonono
Secondary indexesnonoyes
SQL infoSupport of SQLnonoyes infobut no triggers and foreign keys
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Cluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
Supported programming languagesGoC#
C++
Go
Java
JavaScript (Node.js)
Python
Bash
C
C#
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnonoyes
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infohash partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replication infostores two copies of each physical data partition on two separate nodes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno infocan define user-defined aggregate functions for map-reduce-style calculations
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Fine grained access control via users, groups and roles

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More resources
BadgerGoogle Cloud BigtableSingleStore infoformer name was MemSQL
DB-Engines blog posts

Turbocharge Your Application Development Using WebAssembly With SingleStoreDB
17 October 2022,  Akmal Chaudhri, SingleStore (sponsor) 

Cloud-Based Analytics With SingleStoreDB
9 June 2022,  Akmal Chaudhri, SingleStore (sponsor) 

SingleStore: The Increasing Momentum of Multi-Model Database Systems
14 February 2022,  Akmal Chaudhri, SingleStore (sponsor) 

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