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DBMS > EsgynDB vs. Firebase Realtime Database vs. Google Cloud Bigtable vs. IRONdb vs. Postgres-XL

System Properties Comparison EsgynDB vs. Firebase Realtime Database vs. Google Cloud Bigtable vs. IRONdb vs. Postgres-XL

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonIRONdb  Xexclude from comparisonPostgres-XL  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
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.A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityBased on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelRelational DBMSDocument storeKey-value store
Wide column store
Time Series DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
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
Score0.53
Rank#254  Overall
#117  Relational DBMS
Websitewww.esgyn.cnfirebase.google.com/­products/­realtime-databasecloud.google.com/­bigtablewww.circonus.com/solutions/time-series-database/www.postgres-xl.org
Technical documentationfirebase.google.com/­docs/­databasecloud.google.com/­bigtable/­docsdocs.circonus.com/irondb/category/getting-startedwww.postgres-xl.org/­documentation
DeveloperEsgynGoogle infoacquired by Google 2014GoogleCirconus LLC.
Initial release20152012201520172014 infosince 2012, originally named StormDB
Current releaseV0.10.20, January 201810 R1, October 2018
License infoCommercial or Open SourcecommercialcommercialcommercialcommercialOpen Source infoMozilla public license
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 and C++C
Server operating systemsLinuxhostedhostedLinuxLinux
macOS
Data schemeyesschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes infotext, numeric, histogramsyes
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.nonononoyes infoXML type, but no XML query functionality
Secondary indexesyesyesnonoyes
SQL infoSupport of SQLyesnonoSQL-like query language (Circonus Analytics Query Language: CAQL)yes infodistributed, parallel query execution
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)
HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetJava
JavaScript
Objective-C
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresJava Stored Procedureslimited functionality with using 'rules'noyes, in Luauser defined functions
TriggersnoCallbacks are triggered when data changesnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingAutomatic, metric affinity per nodehorizontal partitioning
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 zonesconfigurable replication factor, datacenter aware
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyesnono
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)Immediate consistency per node, eventual consistency across nodesImmediate Consistency
Foreign keys infoReferential integrityyesnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesAtomic single-row operationsnoACID infoMVCC
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.nononono
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)nofine grained access rights according to SQL-standard

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More resources
EsgynDBFirebase Realtime DatabaseGoogle Cloud BigtableIRONdbPostgres-XL
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