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DBMS > Badger vs. BigchainDB vs. Google Cloud Datastore vs. IRONdb vs. PouchDB

System Properties Comparison Badger vs. BigchainDB vs. Google Cloud Datastore vs. IRONdb vs. PouchDB

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonBigchainDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIRONdb  Xexclude from comparisonPouchDB  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.BigchainDB is scalable blockchain database offering decentralization, immutability and native assetsAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityJavaScript DBMS with an API inspired by CouchDB
Primary database modelKey-value storeDocument storeDocument storeTime Series DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score0.79
Rank#212  Overall
#36  Document stores
Score4.47
Rank#76  Overall
#12  Document stores
Score2.28
Rank#115  Overall
#21  Document stores
Websitegithub.com/­dgraph-io/­badgerwww.bigchaindb.comcloud.google.com/­datastorewww.circonus.com/solutions/time-series-database/pouchdb.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerbigchaindb.readthedocs.io/­en/­latestcloud.google.com/­datastore/­docsdocs.circonus.com/irondb/category/getting-startedpouchdb.com/­guides
DeveloperDGraph LabsGoogleCirconus LLC.Apache Software Foundation
Initial release20172016200820172012
Current releaseV0.10.20, January 20187.1.1, June 2019
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoAGPL v3commercialcommercialOpen Source
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoPythonC and C++JavaScript
Server operating systemsBSD
Linux
OS X
Solaris
Windows
LinuxhostedLinuxserver-less, requires a JavaScript environment (browser, Node.js)
Data schemeschema-freeschema-freeschema-freeschema-freeschema-free
Typing infopredefined data types such as float or datenonoyes, details hereyes infotext, numeric, histogramsno
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 indexesnoyesnoyes infovia views
SQL infoSupport of SQLnonoSQL-like query language (GQL)SQL-like query language (Circonus Analytics Query Language: CAQL)no
APIs and other access methodsCLI Client
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP APIHTTP REST infoonly for PouchDB Server
JavaScript API
Supported programming languagesGoGo
Haskell
Java
JavaScript
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
JavaScript
Server-side scripts infoStored proceduresnousing Google App Engineyes, in LuaView functions in JavaScript
TriggersnoCallbacks using the Google Apps Enginenoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingAutomatic, metric affinity per nodeSharding infowith a proxy-based framework, named couchdb-lounge
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factorMulti-source replication using Paxosconfigurable replication factor, datacenter awareMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflownoyes
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 per node, eventual consistency across nodesEventual Consistency
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes,with MongoDB ord RethinkDByesyesyes infoby using IndexedDB, WebSQL or LevelDB as backend
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlnoyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nono

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More resources
BadgerBigchainDBGoogle Cloud DatastoreIRONdbPouchDB
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