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

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

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDragonfly  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
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceA 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 modelDocument store
Relational DBMS
Key-value storeGraph DBMS
Key-value store
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.49
Rank#261  Overall
#38  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
Websitewww.databricks.comgithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
www.graphengine.ioazure.microsoft.com/­services/­synapse-analyticsspark.apache.org/­sql
Technical documentationdocs.databricks.comwww.dragonflydb.io/­docswww.graphengine.io/­docs/­manualdocs.microsoft.com/­azure/­synapse-analyticsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDatabricksDragonflyDB team and community contributorsMicrosoftMicrosoftApache Software Foundation
Initial release20132023201020162014
Current release1.0, March 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoBSL 1.1Open Source infoMIT LicensecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++.NET and CC++Scala
Server operating systemshostedLinux.NEThostedLinux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)scheme-freeyesyesyes
Typing infopredefined data types such as float or datestrings, hashes, lists, sets, sorted sets, bit arraysyesyesyes
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.yesnononono
Secondary indexesyesnoyesno
SQL infoSupport of SQLwith Databricks SQLnonoyesSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Proprietary protocol infoRESP - REdis Serialization ProtocolRESTful HTTP APIADO.NET
JDBC
ODBC
JDBC
ODBC
Supported programming languagesPython
R
Scala
C
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++
F#
Visual Basic
C#
Java
PHP
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesLuayesTransact SQLno
Triggerspublish/subscribe channels provide some trigger functionalitynonono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding, horizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono 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 dataACIDAtomic execution of command blocks and scriptsnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes, strict serializability by the serveryesyesyes
Durability infoSupport for making data persistentyesyesoptional: 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.noyesyesno
User concepts infoAccess controlPassword-based authenticationyesno
More information provided by the system vendor
DatabricksDragonflyGraph Engine infoformer name: TrinityMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSpark SQL
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksDragonflyGraph Engine infoformer name: TrinityMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSpark SQL
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