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DBMS > Dragonfly vs. EsgynDB vs. Firebase Realtime Database vs. Google Cloud Bigtable

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

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Editorial information provided by DB-Engines
NameDragonfly  Xexclude from comparisonEsgynDB  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparison
DescriptionA drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceEnterprise-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.
Primary database modelKey-value storeRelational DBMSDocument storeKey-value store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.41
Rank#266  Overall
#38  Key-value stores
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score14.29
Rank#39  Overall
#6  Document stores
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Websitegithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
www.esgyn.cnfirebase.google.com/­products/­realtime-databasecloud.google.com/­bigtable
Technical documentationwww.dragonflydb.io/­docsfirebase.google.com/­docs/­databasecloud.google.com/­bigtable/­docs
DeveloperDragonflyDB team and community contributorsEsgynGoogle infoacquired by Google 2014Google
Initial release2023201520122015
Current release1.0, March 2023
License infoCommercial or Open SourceOpen Source infoBSL 1.1commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++, Java
Server operating systemsLinuxLinuxhostedhosted
Data schemescheme-freeyesschema-freeschema-free
Typing infopredefined data types such as float or datestrings, hashes, lists, sets, sorted sets, bit arraysyesyesno
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 indexesnoyesyesno
SQL infoSupport of SQLnoyesnono
APIs and other access methodsProprietary protocol infoRESP - REdis Serialization ProtocolADO.NET
JDBC
ODBC
Android
iOS
JavaScript API
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Supported programming languagesC
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl
All languages supporting JDBC/ODBC/ADO.NetJava
JavaScript
Objective-C
C#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresLuaJava Stored Procedureslimited functionality with using 'rules'no
Triggerspublish/subscribe channels provide some trigger functionalitynoCallbacks are triggered when data changesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate 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 integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of command blocks and scriptsACIDyesAtomic single-row operations
Concurrency infoSupport for concurrent manipulation of datayes, strict serializability by the serveryesyesyes
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.yesnono
User concepts infoAccess controlPassword-based authenticationfine 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)

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More resources
DragonflyEsgynDBFirebase Realtime DatabaseGoogle Cloud Bigtable
DB-Engines blog posts

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