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

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

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonBrytlyt  Xexclude from comparisonDatomic  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonQuasardb  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 PostgreSQLDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDistributed, high-performance timeseries database
Primary database modelKey-value storeRelational DBMSRelational DBMSDocument storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score0.29
Rank#288  Overall
#131  Relational DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Websitegithub.com/­dgraph-io/­badgerbrytlyt.iowww.datomic.comcloud.google.com/­datastorequasar.ai
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.brytlyt.iodocs.datomic.comcloud.google.com/­datastore/­docsdoc.quasar.ai/­master
DeveloperDGraph LabsBrytlytCognitectGooglequasardb
Initial release20172016201220082009
Current release5.0, August 20231.0.6735, June 20233.14.1, January 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercial infolimited edition freecommercialcommercial 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 languageGoC, C++ and CUDAJava, ClojureC++
Server operating systemsBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
All OS with a Java VMhostedBSD
Linux
OS X
Windows
Data schemeschema-freeyesyesschema-freeschema-free
Typing infopredefined data types such as float or datenoyesyesyes, 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.noyes infospecific XML-type available, but no XML query functionality.nonono
Secondary indexesnoyesyesyesyes infowith tags
SQL infoSupport of SQLnoyesnoSQL-like query language (GQL)SQL-like query language
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
RESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
Supported programming languagesGo.Net
C
C++
Delphi
Java
Perl
Python
Tcl
Clojure
Java
.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 proceduresnouser defined functions infoin PL/pgSQLyes infoTransaction Functionsusing Google App Engineno
TriggersnoyesBy using transaction functionsCallbacks 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 nodesnoneSource-replica replicationnone infoBut extensive use of caching in the application peersMulti-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 integritynoyesnoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes 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 developmentnoyes infoTransient mode
User concepts infoAccess controlnofine grained access rights according to SQL-standardnoAccess 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
BadgerBrytlytDatomicGoogle Cloud DatastoreQuasardb
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