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DBMS > Badger vs. Google Cloud Datastore vs. SingleStore vs. TigerGraph

System Properties Comparison Badger vs. Google Cloud Datastore vs. SingleStore vs. TigerGraph

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparisonTigerGraph  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformMySQL 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 typeA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelKey-value storeDocument storeRelational DBMSGraph 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
Score3.69
Rank#71  Overall
#12  Document stores
Score4.19
Rank#66  Overall
#36  Relational DBMS
Score1.45
Rank#148  Overall
#14  Graph DBMS
Websitegithub.com/­dgraph-io/­badgercloud.google.com/­datastorewww.singlestore.comwww.tigergraph.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgercloud.google.com/­datastore/­docsdocs.singlestore.comdocs.tigergraph.com
DeveloperDGraph LabsGoogleSingleStore Inc.
Initial release2017200820132017
Current release8.5, January 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercial infofree developer edition availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++, GoC++
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hostedLinux info64 bit version requiredLinux
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or datenoyes, details hereyesyes
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 indexesnoyesyes
SQL infoSupport of SQLnoSQL-like query language (GQL)yes infobut no triggers and foreign keysSQL-like query language (GSQL)
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Cluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesGo.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Bash
C
C#
Java
JavaScript (Node.js)
Python
C++
Java
Server-side scripts infoStored proceduresnousing Google App Engineyesyes
TriggersnoCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infohash partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication using PaxosSource-replica replication infostores two copies of each physical data partition on two separate nodes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowno infocan define user-defined aggregate functions for map-reduce-style calculationsyes
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
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.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
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 rolesRole-based access control

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More resources
BadgerGoogle Cloud DatastoreSingleStore infoformer name was MemSQLTigerGraph
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