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DBMS > Badger vs. Datomic vs. Google Cloud Firestore vs. Hypertable vs. Kdb

System Properties Comparison Badger vs. Datomic vs. Google Cloud Firestore vs. Hypertable vs. Kdb

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonDatomic  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonHypertable  Xexclude from comparisonKdb  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
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 durabilityCloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.An open source BigTable implementation based on distributed file systems such as HadoopHigh performance Time Series DBMS
Primary database modelKey-value storeRelational DBMSDocument storeWide column storeTime Series DBMS
Vector DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score7.85
Rank#51  Overall
#8  Document stores
Score7.55
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Websitegithub.com/­dgraph-io/­badgerwww.datomic.comfirebase.google.com/­products/­firestorekx.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.datomic.comfirebase.google.com/­docs/­firestorecode.kx.com
DeveloperDGraph LabsCognitectGoogleHypertable Inc.Kx Systems, a division of First Derivatives plc
Initial release20172012201720092000 infokdb was released 2000, kdb+ in 2003
Current release1.0.6735, June 20230.9.8.11, March 20163.6, May 2018
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial infolimited edition freecommercialOpen Source infoGNU version 3. Commercial license availablecommercial infofree 32-bit version
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoJava, ClojureC++q
Server operating systemsBSD
Linux
OS X
Solaris
Windows
All OS with a Java VMhostedLinux
OS X
Windows infoan inofficial Windows port is available
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or datenoyesyesnoyes
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.nononoyes
Secondary indexesnoyesyesrestricted infoonly exact value or prefix value scansyes infotable attribute 'grouped'
SQL infoSupport of SQLnonononoSQL-like query language (q)
APIs and other access methodsRESTful HTTP APIAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
C++ API
Thrift
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
Supported programming languagesGoClojure
Java
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C++
Java
Perl
PHP
Python
Ruby
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infoTransaction Functionsyes, Firebase Rules & Cloud Functionsnouser defined functions
TriggersnoBy using transaction functionsyes, with Cloud Functionsnoyes infowith views
Partitioning methods infoMethods for storing different data on different nodesnonenone infoBut extensive use of caching in the application peersShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnonenone infoBut extensive use of caching in the application peersMulti-source replicationselectable replication factor on file system levelSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoUsing Cloud Dataflowyesno infosimilar paradigm used for internal processing
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDyesnono
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
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 developmentyes
User concepts infoAccess controlnonoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.norights management via user accounts
More information provided by the system vendor
BadgerDatomicGoogle Cloud FirestoreHypertableKdb
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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More resources
BadgerDatomicGoogle Cloud FirestoreHypertableKdb
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