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DBMS > Badger vs. Datomic vs. etcd vs. Google Cloud Datastore vs. Quasardb

System Properties Comparison Badger vs. Datomic vs. etcd vs. Google Cloud Datastore vs. Quasardb

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonDatomic  Xexclude from comparisonetcd  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonQuasardb  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA distributed reliable key-value storeAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDistributed, high-performance timeseries database
Primary database modelKey-value storeRelational DBMSKey-value storeDocument storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#320  Overall
#47  Key-value stores
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score7.03
Rank#54  Overall
#5  Key-value stores
Score4.36
Rank#72  Overall
#12  Document stores
Score0.21
Rank#322  Overall
#29  Time Series DBMS
Websitegithub.com/­dgraph-io/­badgerwww.datomic.cometcd.io
github.com/­etcd-io/­etcd
cloud.google.com/­datastorequasar.ai
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.datomic.cometcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
cloud.google.com/­datastore/­docsdoc.quasar.ai/­master
DeveloperDGraph LabsCognitectGooglequasardb
Initial release2017201220082009
Current release1.0.6735, June 20233.4, August 20193.14.1, January 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial infolimited edition freeOpen Source infoApache Version 2.0commercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJava, ClojureGoC++
Server operating systemsBSD
Linux
OS X
Solaris
Windows
All OS with a Java VMFreeBSD
Linux
Windows infoexperimental
hostedBSD
Linux
OS X
Windows
Data schemeschema-freeyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or datenoyesnoyes, details hereyes infointeger and binary
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 indexesnoyesnoyesyes infowith tags
SQL infoSupport of SQLnononoSQL-like query language (GQL)SQL-like query language
APIs and other access methodsRESTful HTTP APIgRPC
JSON over HTTP
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
Supported programming languagesGoClojure
Java
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresnoyes infoTransaction Functionsnousing Google App Engineno
TriggersnoBy using transaction functionsyes, watching key changesCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesnonenone infoBut extensive use of caching in the application peersShardingSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesnonenone infoBut extensive use of caching in the application peersUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replication using PaxosSource-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes infousing Google Cloud Dataflowwith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate ConsistencyImmediate 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 integritynononoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentnonoyes infoTransient mode
User concepts infoAccess controlnononoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Cryptographically strong user authentication and audit trail

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More resources
BadgerDatomicetcdGoogle Cloud DatastoreQuasardb
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