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DBMS > Dragonfly vs. Firebase Realtime Database vs. Geode vs. Microsoft Azure Data Explorer vs. TimesTen

System Properties Comparison Dragonfly vs. Firebase Realtime Database vs. Geode vs. Microsoft Azure Data Explorer vs. TimesTen

Editorial information provided by DB-Engines
NameDragonfly  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGeode  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTimesTen  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 instanceCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesFully managed big data interactive analytics platformIn-Memory RDBMS compatible to Oracle
Primary database modelKey-value storeDocument storeKey-value storeRelational DBMS infocolumn orientedRelational DBMS
Secondary database modelsDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.49
Rank#261  Overall
#38  Key-value stores
Score13.64
Rank#39  Overall
#6  Document stores
Score1.86
Rank#134  Overall
#24  Key-value stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score1.36
Rank#161  Overall
#75  Relational DBMS
Websitegithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
firebase.google.com/­products/­realtime-databasegeode.apache.orgazure.microsoft.com/­services/­data-explorerwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationwww.dragonflydb.io/­docsfirebase.google.com/­docs/­databasegeode.apache.org/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­database/­timesten-18.1
DeveloperDragonflyDB team and community contributorsGoogle infoacquired by Google 2014Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.MicrosoftOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20232012200220191998
Current release1.0, March 20231.1, February 2017cloud service with continuous releases11 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourceOpen Source infoBSL 1.1commercialOpen Source infoApache Version 2; commercial licenses available as Gemfirecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java
Server operating systemsLinuxhostedAll OS with a Java VM infothe JDK (8 or later) is also requiredhostedAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemescheme-freeschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or datestrings, hashes, lists, sets, sorted sets, bit arraysyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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.nononoyesno
Secondary indexesnoyesnoall fields are automatically indexedyes
SQL infoSupport of SQLnonoSQL-like query language (OQL)Kusto Query Language (KQL), SQL subsetyes
APIs and other access methodsProprietary protocol infoRESP - REdis Serialization ProtocolAndroid
iOS
JavaScript API
RESTful HTTP API
Java Client API
Memcached protocol
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
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
Java
JavaScript
Objective-C
.Net
All JVM based languages
C++
Groovy
Java
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresLualimited functionality with using 'rules'user defined functionsYes, possible languages: KQL, Python, RPL/SQL
Triggerspublish/subscribe channels provide some trigger functionalityCallbacks are triggered when data changesyes infoCache Event Listenersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Eventual ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of command blocks and scriptsyesyes, on a single nodenoACID
Concurrency infoSupport for concurrent manipulation of datayes, strict serializability by the serveryesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes
User concepts infoAccess controlPassword-based authenticationyes, based on authentication and database rulesAccess rights per client and object definableAzure Active Directory Authenticationfine grained access rights according to SQL-standard

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More resources
DragonflyFirebase Realtime DatabaseGeodeMicrosoft Azure Data ExplorerTimesTen
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