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DBMS > CouchDB vs. Google Cloud Datastore vs. HarperDB vs. Splunk

System Properties Comparison CouchDB vs. Google Cloud Datastore vs. HarperDB vs. Splunk

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Editorial information provided by DB-Engines
NameCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHarperDB  Xexclude from comparisonSplunk  Xexclude from comparison
DescriptionA native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformHarperDB takes the "stack" out of "tech stack" by combining an ultra-fast document-style data store, in-memory cache, real-time message broker, and your application components into a single distributed technology.Analytics Platform for Big Data
Primary database modelDocument storeDocument storeDocument storeSearch engine
Secondary database modelsSpatial DBMS infousing the Geocouch extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.46
Rank#51  Overall
#7  Document stores
Score4.13
Rank#71  Overall
#12  Document stores
Score0.55
Rank#243  Overall
#38  Document stores
Score93.02
Rank#13  Overall
#2  Search engines
Websitecouchdb.apache.orgcloud.google.com/­datastorewww.harperdb.iowww.splunk.com
Technical documentationdocs.couchdb.org/­en/­stablecloud.google.com/­datastore/­docsdocs.harperdb.io/­docsdocs.splunk.com/­Documentation/­Splunk
DeveloperApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerGoogleHarperDBSplunk Inc.
Initial release2005200820172003
Current release3.3.3, December 20233.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache version 2commercialcommercial infofree community edition availablecommercial infoLimited free edition and free developer edition available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageErlangNode.js
Server operating systemsAndroid
BSD
Linux
OS X
Solaris
Windows
hostedLinux
OS X
Linux
OS X
Solaris
Windows
Data schemeschema-freeschema-freedynamic schemayes
Typing infopredefined data types such as float or datenoyes, details hereyes infoJSON data typesyes
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 indexesyes infovia viewsyesyesyes
SQL infoSupport of SQLnoSQL-like query language (GQL)SQL-like data manipulation statementsno infoSplunk Search Processing Language for search commands
APIs and other access methodsRESTful HTTP/JSON APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
HTTP REST
Supported programming languagesC
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
C#
Java
JavaScript
PHP
Python
Ruby
Server-side scripts infoStored proceduresView functions in JavaScriptusing Google App EngineCustom Functions infosince release 3.1yes
TriggersyesCallbacks using the Google Apps Enginenoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoimproved architecture with release 2.0ShardingA table resides as a whole on one (or more) nodes in a clusterSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication using Paxosyes infothe nodes on which a table resides can be definedMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infousing Google Cloud Dataflownoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual 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 ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoatomic operations within a single document possibleACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsAtomic execution of specific operationsno infoA 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching
Concurrency infoSupport for concurrent manipulation of datayes infostrategy: optimistic lockingyesyesyes
Durability infoSupport for making data persistentyesyesyes, using LMDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlAccess rights for users can be defined per databaseAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and rolesAccess rights for users and roles

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More resources
CouchDB infostands for "Cluster Of Unreliable Commodity Hardware"Google Cloud DatastoreHarperDBSplunk
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