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DBMS > Axibase vs. FatDB vs. Google Cloud Datastore vs. PouchDB vs. Warp 10

System Properties Comparison Axibase vs. FatDB vs. Google Cloud Datastore vs. PouchDB vs. Warp 10

Editorial information provided by DB-Engines
NameAxibase  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonPouchDB  Xexclude from comparisonWarp 10  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionScalable TimeSeries DBMS based on HBase with integrated rule engine and visualizationA .NET NoSQL DBMS that can integrate with and extend SQL Server.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformJavaScript DBMS with an API inspired by CouchDBTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelTime Series DBMSDocument store
Key-value store
Document storeDocument storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.32
Rank#288  Overall
#25  Time Series DBMS
Score4.49
Rank#79  Overall
#12  Document stores
Score2.35
Rank#116  Overall
#22  Document stores
Score0.08
Rank#358  Overall
#35  Time Series DBMS
Websiteaxibase.com/­docs/­atsd/­financecloud.google.com/­datastorepouchdb.comwww.warp10.io
Technical documentationcloud.google.com/­datastore/­docspouchdb.com/­guideswww.warp10.io/­content/­02_Getting_started
DeveloperAxibase CorporationFatCloudGoogleApache Software FoundationSenX
Initial release20132012200820122015
Current release155857.1.1, June 2019
License infoCommercial or Open Sourcecommercial infoCommunity Edition (single node) is free, Enterprise Edition (distributed) is paidcommercialcommercialOpen SourceOpen Source infoApache License 2.0
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 languageJavaC#JavaScriptJava
Server operating systemsLinuxWindowshostedserver-less, requires a JavaScript environment (browser, Node.js)Linux
OS X
Windows
Data schemeyesschema-freeschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyes infoshort, integer, long, float, double, decimal, stringyesyes, details herenoyes
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.nononono
Secondary indexesnoyesyesyes infovia viewsno
SQL infoSupport of SQLSQL-like query languageno infoVia inetgration in SQL ServerSQL-like query language (GQL)nono
APIs and other access methodsJDBC
Proprietary protocol (Network API)
RESTful HTTP API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP REST infoonly for PouchDB Server
JavaScript API
HTTP API
Jupyter
WebSocket
Supported programming languagesGo
Java
PHP
Python
R
Ruby
C#.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
JavaScript
Server-side scripts infoStored proceduresyesyes infovia applicationsusing Google App EngineView functions in JavaScriptyes infoWarpScript
Triggersyesyes infovia applicationsCallbacks using the Google Apps Engineyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infowith a proxy-based framework, named couchdb-loungeSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factorMulti-source replication using PaxosMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
selectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesyes infousing Google Cloud Dataflowyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate 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.Eventual ConsistencyImmediate Consistency infobased on HBase
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlno infoCan implement custom security layer via applicationsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noMandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
AxibaseFatDBGoogle Cloud DatastorePouchDBWarp 10
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