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DBMS > Apache Druid vs. FatDB vs. Google Cloud Firestore vs. Splice Machine vs. Yaacomo

System Properties Comparison Apache Druid vs. FatDB vs. Google Cloud Firestore vs. Splice Machine vs. Yaacomo

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonSplice Machine  Xexclude from comparisonYaacomo  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.Yaacomo seems to be discontinued and is removed from the DB-Engines 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.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMS
Time Series DBMS
Document store
Key-value store
Document storeRelational DBMSRelational 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
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitedruid.apache.orgfirebase.google.com/­products/­firestoresplicemachine.comyaacomo.com
Technical documentationdruid.apache.org/­docs/­latest/­designfirebase.google.com/­docs/­firestoresplicemachine.com/­how-it-works
DeveloperApache Software Foundation and contributorsFatCloudGoogleSplice MachineQ2WEB GmbH
Initial release20122012201720142009
Current release29.0.1, April 20243.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercialOpen Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC#Java
Server operating systemsLinux
OS X
Unix
WindowshostedLinux
OS X
Solaris
Windows
Android
Linux
Windows
Data schemeyes infoschema-less columns are supportedschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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 indexesyesyesyesyesyes
SQL infoSupport of SQLSQL for queryingno infoVia inetgration in SQL Servernoyesyes
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
JDBC
Native Spark Datasource
ODBC
JDBC
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C#Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infovia applicationsyes, Firebase Rules & Cloud Functionsyes infoJava
Triggersnoyes infovia applicationsyes, with Cloud Functionsyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioninghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication factorMulti-source replicationMulti-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesUsing Cloud DataflowYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoyesACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
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.Access rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Apache DruidFatDBGoogle Cloud FirestoreSplice MachineYaacomo
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