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DBMS > Dragonfly vs. Faircom EDGE vs. Microsoft Azure Data Explorer vs. Sphinx vs. Splice Machine

System Properties Comparison Dragonfly vs. Faircom EDGE vs. Microsoft Azure Data Explorer vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameDragonfly  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  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 instanceFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsFully managed big data interactive analytics platformOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value storeKey-value store
Relational DBMS
Relational DBMS infocolumn orientedSearch engineRelational 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
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitegithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
www.faircom.com/­products/­faircom-edgeazure.microsoft.com/­services/­data-explorersphinxsearch.comsplicemachine.com
Technical documentationwww.dragonflydb.io/­docsdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmldocs.microsoft.com/­en-us/­azure/­data-explorersphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperDragonflyDB team and community contributorsFairCom CorporationMicrosoftSphinx Technologies Inc.Splice Machine
Initial release20231979201920012014
Current release1.0, March 2023V3, October 2020cloud service with continuous releases3.5.1, February 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoBSL 1.1commercial infoRestricted, free version availablecommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ANSI C, C++C++Java
Server operating systemsLinuxAndroid
Linux infoARM, x86
Raspbian
Windows
hostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemescheme-freeFlexible Schema (defined schema, partial schema, schema free)Fixed schema with schema-less datatypes (dynamic)yesyes
Typing infopredefined data types such as float or datestrings, hashes, lists, sets, sorted sets, bit arraysyes, ANSI Standard SQL Typesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesnoyes
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.noyesyes
Secondary indexesnoyesall fields are automatically indexedyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoyes infoANSI SQL queriesKusto Query Language (KQL), SQL subsetSQL-like query language (SphinxQL)yes
APIs and other access methodsProprietary protocol infoRESP - REdis Serialization ProtocolADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Proprietary protocolJDBC
Native Spark Datasource
ODBC
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
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresLuayes info.Net, JavaScript, C/C++Yes, possible languages: KQL, Python, Rnoyes infoJava
Triggerspublish/subscribe channels provide some trigger functionalityyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes
Partitioning methods infoMethods for storing different data on different nodesFile partitioning infoCustomizable business rules for partitioningSharding infoImplicit feature of the cloud serviceSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoSynchronous and asynchronous realtime replication based on transaction logsyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Tunable Consistency
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infowhen using SQLnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of command blocks and scriptsACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayes, strict serializability by the serveryes infoacross SQL and NoSQLyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
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 authenticationFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Azure Active Directory AuthenticationnoAccess rights for users, groups and roles according to SQL-standard

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More resources
DragonflyFaircom EDGE infoformerly c-treeEDGEMicrosoft Azure Data ExplorerSphinxSplice Machine
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