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DBMS > Geode vs. Google Cloud Bigtable vs. PouchDB vs. Sphinx

System Properties Comparison Geode vs. Google Cloud Bigtable vs. PouchDB vs. Sphinx

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Editorial information provided by DB-Engines
NameGeode  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonPouchDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionGeode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.JavaScript DBMS with an API inspired by CouchDBOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelKey-value storeKey-value store
Wide column store
Document storeSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.86
Rank#134  Overall
#24  Key-value stores
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score2.34
Rank#112  Overall
#21  Document stores
Score5.95
Rank#55  Overall
#5  Search engines
Websitegeode.apache.orgcloud.google.com/­bigtablepouchdb.comsphinxsearch.com
Technical documentationgeode.apache.org/­docscloud.google.com/­bigtable/­docspouchdb.com/­guidessphinxsearch.com/­docs
DeveloperOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.GoogleApache Software FoundationSphinx Technologies Inc.
Initial release2002201520122001
Current release1.1, February 20177.1.1, June 20193.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses available as GemfirecommercialOpen SourceOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaScriptC++
Server operating systemsAll OS with a Java VM infothe JDK (8 or later) is also requiredhostedserver-less, requires a JavaScript environment (browser, Node.js)FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnonono
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 indexesnonoyes infovia viewsyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query language (OQL)nonoSQL-like query language (SphinxQL)
APIs and other access methodsJava Client API
Memcached protocol
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP REST infoonly for PouchDB Server
JavaScript API
Proprietary protocol
Supported programming languages.Net
All JVM based languages
C++
Groovy
Java
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
JavaScriptC++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresuser defined functionsnoView functions in JavaScriptno
Triggersyes infoCache Event Listenersnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infowith a proxy-based framework, named couchdb-loungeSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes, on a single nodeAtomic single-row operationsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyes 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.yesnoyes
User concepts infoAccess controlAccess rights per client and object definableAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nono

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GeodeGoogle Cloud BigtablePouchDBSphinx
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