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DBMS > Apache Kylin vs. CrateDB vs. FatDB vs. Google Cloud Firestore

System Properties Comparison Apache Kylin vs. CrateDB vs. FatDB vs. Google Cloud Firestore

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Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonCrateDB  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackDistributed Database based on LuceneA .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.
Primary database modelRelational DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Document store
Key-value store
Document store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.25
Rank#170  Overall
#77  Relational DBMS
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#10  Vector DBMS
Score7.36
Rank#53  Overall
#9  Document stores
Websitekylin.apache.orgcratedb.comfirebase.google.com/­products/­firestore
Technical documentationkylin.apache.org/­docscratedb.com/­docsfirebase.google.com/­docs/­firestore
DeveloperApache Software Foundation, originally contributed from eBay IncCrateFatCloudGoogle
Initial release2015201320122017
Current release3.1.0, July 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Sourcecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC#
Server operating systemsLinuxAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportWindowshosted
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesyes
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
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)yes, but no triggers and constraints, and PostgreSQL compatibilityno infoVia inetgration in SQL Serverno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Supported programming languages.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
C#Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
Server-side scripts infoStored proceduresuser defined functions (Javascript)yes infovia applicationsyes, Firebase Rules & Cloud Functions
Triggersnoyes infovia applicationsyes, with Cloud Functions
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelselectable replication factorMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyesUsing Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Read-after-write consistency on record level
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infounique row identifiers can be used for implementing an optimistic concurrency control strategynoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlrights management via user accountsno 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.

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More resources
Apache KylinCrateDBFatDBGoogle Cloud Firestore
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