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DBMS > Apache Druid vs. FatDB vs. Google Cloud Firestore vs. Quasardb

System Properties Comparison Apache Druid vs. FatDB vs. Google Cloud Firestore vs. Quasardb

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonQuasardb  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.Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.Distributed, high-performance timeseries database
Primary database modelRelational DBMS
Time Series DBMS
Document store
Key-value store
Document storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score7.85
Rank#51  Overall
#8  Document stores
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Websitedruid.apache.orgfirebase.google.com/­products/­firestorequasar.ai
Technical documentationdruid.apache.org/­docs/­latest/­designfirebase.google.com/­docs/­firestoredoc.quasar.ai/­master
DeveloperApache Software Foundation and contributorsFatCloudGooglequasardb
Initial release2012201220172009
Current release29.0.1, April 20243.14.1, January 2024
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC#C++
Server operating systemsLinux
OS X
Unix
WindowshostedBSD
Linux
OS X
Windows
Data schemeyes infoschema-less columns are supportedschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesyes infointeger and binary
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 indexesyesyesyesyes infowith tags
SQL infoSupport of SQLSQL for queryingno infoVia inetgration in SQL ServernoSQL-like query language
APIs and other access methodsJDBC
RESTful HTTP/JSON API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C#Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresnoyes infovia applicationsyes, Firebase Rules & Cloud Functionsno
Triggersnoyes infovia applicationsyes, with Cloud Functionsno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardingSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication factorMulti-source replicationSource-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesUsing Cloud Dataflowwith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoyesACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoTransient mode
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. Security Rules for 3rd party authentication using Firebase Auth.Cryptographically strong user authentication and audit trail

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More resources
Apache DruidFatDBGoogle Cloud FirestoreQuasardb
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