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DBMS > Apache Druid vs. FatDB vs. Google Cloud Datastore vs. Hawkular Metrics vs. PouchDB

System Properties Comparison Apache Druid vs. FatDB vs. Google Cloud Datastore vs. Hawkular Metrics vs. PouchDB

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonPouchDB  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA .NET NoSQL DBMS that can integrate with and extend SQL Server.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.JavaScript DBMS with an API inspired by CouchDB
Primary database modelRelational DBMS
Time Series DBMS
Document store
Key-value store
Document storeTime Series DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score2.34
Rank#112  Overall
#21  Document stores
Websitedruid.apache.orgcloud.google.com/­datastorewww.hawkular.orgpouchdb.com
Technical documentationdruid.apache.org/­docs/­latest/­designcloud.google.com/­datastore/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidepouchdb.com/­guides
DeveloperApache Software Foundation and contributorsFatCloudGoogleCommunity supported by Red HatApache Software Foundation
Initial release20122012200820142012
Current release29.0.1, April 20247.1.1, June 2019
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercialOpen Source infoApache 2.0Open Source
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC#JavaJavaScript
Server operating systemsLinux
OS X
Unix
WindowshostedLinux
OS X
Windows
server-less, requires a JavaScript environment (browser, Node.js)
Data schemeyes infoschema-less columns are supportedschema-freeschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes, details hereyesno
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 indexesyesyesyesnoyes infovia views
SQL infoSupport of SQLSQL for queryingno infoVia inetgration in SQL ServerSQL-like query language (GQL)nono
APIs and other access methodsJDBC
RESTful HTTP/JSON API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP RESTHTTP REST infoonly for PouchDB Server
JavaScript API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C#.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
Python
Ruby
JavaScript
Server-side scripts infoStored proceduresnoyes infovia applicationsusing Google App EnginenoView functions in JavaScript
Triggersnoyes infovia applicationsCallbacks using the Google Apps Engineyes infovia Hawkular Alertingyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardingSharding infobased on CassandraSharding infowith a proxy-based framework, named couchdb-lounge
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication factorMulti-source replication using Paxosselectable replication factor infobased on CassandraMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infousing Google Cloud Dataflownoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual 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 Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
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 persistentyesyesyesyesyes 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 controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemno infoCan implement custom security layer via applicationsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nono

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More resources
Apache DruidFatDBGoogle Cloud DatastoreHawkular MetricsPouchDB
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