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DBMS > Axibase vs. CouchDB vs. Google Cloud Datastore vs. Sphinx

System Properties Comparison Axibase vs. CouchDB vs. Google Cloud Datastore vs. Sphinx

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Editorial information provided by DB-Engines
NameAxibase  Xexclude from comparisonCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionScalable TimeSeries DBMS based on HBase with integrated rule engine and visualizationA 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 PlatformOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelTime Series DBMSDocument storeDocument storeSearch engine
Secondary database modelsSpatial DBMS infousing the Geocouch extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.33
Rank#292  Overall
#25  Time Series DBMS
Score11.73
Rank#45  Overall
#7  Document stores
Score4.87
Rank#78  Overall
#12  Document stores
Score6.06
Rank#61  Overall
#6  Search engines
Websiteaxibase.com/­docs/­atsd/­financecouchdb.apache.orgcloud.google.com/­datastoresphinxsearch.com
Technical documentationdocs.couchdb.org/­en/­stablecloud.google.com/­datastore/­docssphinxsearch.com/­docs
DeveloperAxibase CorporationApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerGoogleSphinx Technologies Inc.
Initial release2013200520082001
Current release155853.3.3, December 20233.5.1, February 2023
License infoCommercial or Open Sourcecommercial infoCommunity Edition (single node) is free, Enterprise Edition (distributed) is paidOpen Source infoApache version 2commercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaErlangC++
Server operating systemsLinuxAndroid
BSD
Linux
OS X
Solaris
Windows
hostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyes infoshort, integer, long, float, double, decimal, stringnoyes, details hereno
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.nonono
Secondary indexesnoyes infovia viewsyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query languagenoSQL-like query language (GQL)SQL-like query language (SphinxQL)
APIs and other access methodsJDBC
Proprietary protocol (Network API)
RESTful HTTP API
RESTful HTTP/JSON APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Proprietary protocol
Supported programming languagesGo
Java
PHP
Python
R
Ruby
C
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
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyesView functions in JavaScriptusing Google App Engineno
TriggersyesyesCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoimproved architecture with release 2.0ShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
Multi-source replication using Paxosnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesyes infousing Google Cloud Dataflowno
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.
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infoatomic operations within a single document possibleACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
Concurrency infoSupport for concurrent manipulation of datayesyes infostrategy: optimistic lockingyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
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)no

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More resources
AxibaseCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"Google Cloud DatastoreSphinx
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