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DBMS > EsgynDB vs. Firebase Realtime Database vs. Google Cloud Bigtable vs. Netezza vs. Sphinx

System Properties Comparison EsgynDB vs. Firebase Realtime Database vs. Google Cloud Bigtable vs. Netezza vs. Sphinx

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSphinx  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.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 PureSystemsOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSDocument storeKey-value store
Wide column store
Relational DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
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
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitewww.esgyn.cnfirebase.google.com/­products/­realtime-databasecloud.google.com/­bigtablewww.ibm.com/­products/­netezzasphinxsearch.com
Technical documentationfirebase.google.com/­docs/­databasecloud.google.com/­bigtable/­docssphinxsearch.com/­docs
DeveloperEsgynGoogle infoacquired by Google 2014GoogleIBMSphinx Technologies Inc.
Initial release20152012201520002001
Current release3.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialcommercialcommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaC++
Server operating systemsLinuxhostedhostedLinux infoincluded in applianceFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnoyesno
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 indexesyesyesnoyesyes infofull-text index on all search fields
SQL infoSupport of SQLyesnonoyesSQL-like query language (SphinxQL)
APIs and other access methodsADO.NET
JDBC
ODBC
Android
iOS
JavaScript API
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
OLE DB
Proprietary protocol
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetJava
JavaScript
Objective-C
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C++
Fortran
Java
Lua
Perl
Python
R
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresJava Stored Procedureslimited functionality with using 'rules'noyesno
TriggersnoCallbacks are triggered when data changesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyesyesno
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 consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesAtomic single-row operationsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
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 rulesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users with fine-grained authorization conceptno

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More resources
EsgynDBFirebase Realtime DatabaseGoogle Cloud BigtableNetezza infoAlso called PureData System for Analytics by IBMSphinx
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