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DBMS > EsgynDB vs. Firebase Realtime Database vs. Fujitsu Enterprise Postgres vs. Google Cloud Bigtable vs. Netezza

System Properties Comparison EsgynDB vs. Firebase Realtime Database vs. Fujitsu Enterprise Postgres vs. Google Cloud Bigtable vs. Netezza

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Data warehouse and analytics appliance part of IBM PureSystems
Primary database modelRelational DBMSDocument storeRelational DBMSKey-value store
Wide column store
Relational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.15
Rank#325  Overall
#144  Relational DBMS
Score13.60
Rank#39  Overall
#6  Document stores
Score0.22
Rank#304  Overall
#137  Relational DBMS
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Score7.56
Rank#48  Overall
#31  Relational DBMS
Websitewww.esgyn.cnfirebase.google.com/­products/­realtime-databasewww.postgresql.fastware.comcloud.google.com/­bigtablewww.ibm.com/­products/­netezza
Technical documentationfirebase.google.com/­docs/­databasewww.postgresql.fastware.com/­product-manualscloud.google.com/­bigtable/­docs
DeveloperEsgynGoogle infoacquired by Google 2014PostgreSQL Global Development Group, Fujitsu Australia Software TechnologyGoogleIBM
Initial release2015201220152000
Current releaseFujitsu Enterprise Postgres 14, January 2022
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaC
Server operating systemsLinuxhostedLinux
Windows
hostedLinux infoincluded in appliance
Data schemeyesschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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 indexesyesyesyesnoyes
SQL infoSupport of SQLyesnoyesnoyes
APIs and other access methodsADO.NET
JDBC
ODBC
Android
iOS
JavaScript API
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
OLE DB
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetJava
JavaScript
Objective-C
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresJava Stored Procedureslimited functionality with using 'rules'user defined functionsnoyes
TriggersnoCallbacks are triggered when data changesyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingpartitioning by range, list and by hashShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersSource-replica replicationInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integrityyesnoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesACIDAtomic single-row operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes
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.nono
User concepts infoAccess controlfine grained access rights according to SQL-standardyes, based on authentication and database rulesfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users with fine-grained authorization concept

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More resources
EsgynDBFirebase Realtime DatabaseFujitsu Enterprise PostgresGoogle Cloud BigtableNetezza infoAlso called PureData System for Analytics by IBM
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