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DBMS > Dragonfly vs. Ehcache vs. Graph Engine vs. Microsoft Azure Synapse Analytics vs. Spark SQL

System Properties Comparison Dragonfly vs. Ehcache vs. Graph Engine vs. Microsoft Azure Synapse Analytics vs. Spark SQL

Editorial information provided by DB-Engines
NameDragonfly  Xexclude from comparisonEhcache  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSpark SQL  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 instanceA widely adopted Java cache with tiered storage optionsA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeKey-value storeGraph DBMS
Key-value store
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.49
Rank#261  Overall
#38  Key-value stores
Score4.64
Rank#68  Overall
#8  Key-value stores
Score0.67
Rank#232  Overall
#21  Graph DBMS
#34  Key-value stores
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
www.ehcache.orgwww.graphengine.ioazure.microsoft.com/­services/­synapse-analyticsspark.apache.org/­sql
Technical documentationwww.dragonflydb.io/­docswww.ehcache.org/­documentationwww.graphengine.io/­docs/­manualdocs.microsoft.com/­azure/­synapse-analyticsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDragonflyDB team and community contributorsTerracotta Inc, owned by Software AGMicrosoftMicrosoftApache Software Foundation
Initial release20232009201020162014
Current release1.0, March 20233.10.0, March 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoBSL 1.1Open Source infoApache Version 2; commercial licenses availableOpen Source infoMIT LicensecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java.NET and CC++Scala
Server operating systemsLinuxAll OS with a Java VM.NEThostedLinux
OS X
Windows
Data schemescheme-freeschema-freeyesyesyes
Typing infopredefined data types such as float or datestrings, hashes, lists, sets, sorted sets, bit arraysyesyesyesyes
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.nonononono
Secondary indexesnonoyesno
SQL infoSupport of SQLnononoyesSQL-like DML and DDL statements
APIs and other access methodsProprietary protocol infoRESP - REdis Serialization ProtocolJCacheRESTful HTTP APIADO.NET
JDBC
ODBC
JDBC
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
JavaC#
C++
F#
Visual Basic
C#
Java
PHP
Java
Python
R
Scala
Server-side scripts infoStored proceduresLuanoyesTransact SQLno
Triggerspublish/subscribe channels provide some trigger functionalityyes infoCache Event Listenersnonono
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta Serverhorizontal partitioningSharding, horizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoby using Terracotta Serveryesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyTunable Consistency (Strong, Eventual, Weak)Immediate Consistency
Foreign keys infoReferential integritynononono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of command blocks and scriptsyes infosupports JTA and can work as an XA resourcenoACIDno
Concurrency infoSupport for concurrent manipulation of datayes, strict serializability by the serveryesyesyesyes
Durability infoSupport for making data persistentyesyes infousing a tiered cache-storage approachoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesno
User concepts infoAccess controlPassword-based authenticationnoyesno

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More resources
DragonflyEhcacheGraph Engine infoformer name: TrinityMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSpark SQL
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