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DBMS > Apache Phoenix vs. EsgynDB vs. FatDB vs. Firebase Realtime Database vs. Google Cloud Bigtable

System Properties Comparison Apache Phoenix vs. EsgynDB vs. FatDB vs. Firebase Realtime Database vs. Google Cloud Bigtable

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonEsgynDB  Xexclude from comparisonFatDB  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionA .NET NoSQL DBMS that can integrate with and extend SQL Server.Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.
Primary database modelRelational DBMSRelational DBMSDocument store
Key-value store
Document storeKey-value store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score13.64
Rank#39  Overall
#6  Document stores
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Websitephoenix.apache.orgwww.esgyn.cnfirebase.google.com/­products/­realtime-databasecloud.google.com/­bigtable
Technical documentationphoenix.apache.orgfirebase.google.com/­docs/­databasecloud.google.com/­bigtable/­docs
DeveloperApache Software FoundationEsgynFatCloudGoogle infoacquired by Google 2014Google
Initial release20142015201220122015
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, JavaC#
Server operating systemsLinux
Unix
Windows
LinuxWindowshostedhosted
Data schemeyes infolate-bound, schema-on-read capabilitiesyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesyesno
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 indexesyesyesyesyesno
SQL infoSupport of SQLyesyesno infoVia inetgration in SQL Servernono
APIs and other access methodsJDBCADO.NET
JDBC
ODBC
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Android
iOS
JavaScript API
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
All languages supporting JDBC/ODBC/ADO.NetC#Java
JavaScript
Objective-C
C#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functionsJava Stored Proceduresyes infovia applicationslimited functionality with using 'rules'no
Triggersnonoyes infovia applicationsCallbacks are triggered when data changesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication between multi datacentersselectable replication factorInternal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyesyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoyesAtomic single-row operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.yesnono
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyfine grained access rights according to SQL-standardno infoCan implement custom security layer via applicationsyes, based on authentication and database rulesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Apache PhoenixEsgynDBFatDBFirebase Realtime DatabaseGoogle Cloud Bigtable
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