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DBMS > Apache Druid vs. Microsoft Azure Synapse Analytics vs. Spark SQL vs. Stardog vs. Vitess

System Properties Comparison Apache Druid vs. Microsoft Azure Synapse Analytics vs. Spark SQL vs. Stardog vs. Vitess

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSpark SQL  Xexclude from comparisonStardog  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataElastic, 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 processingEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualizationScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSRelational DBMSGraph DBMS
RDF store
Relational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score2.07
Rank#122  Overall
#11  Graph DBMS
#6  RDF stores
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websitedruid.apache.orgazure.microsoft.com/­services/­synapse-analyticsspark.apache.org/­sqlwww.stardog.comvitess.io
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.microsoft.com/­azure/­synapse-analyticsspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.stardog.comvitess.io/­docs
DeveloperApache Software Foundation and contributorsMicrosoftApache Software FoundationStardog-UnionThe Linux Foundation, PlanetScale
Initial release20122016201420102013
Current release29.0.1, April 20243.5.0 ( 2.13), September 20237.3.0, May 202015.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoApache 2.0commercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/studentsOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++ScalaJavaGo
Server operating systemsLinux
OS X
Unix
hostedLinux
OS X
Windows
Linux
macOS
Windows
Docker
Linux
macOS
Data schemeyes infoschema-less columns are supportedyesyesschema-free and OWL/RDFS-schema supportyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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 infoImport/export of XML data possible
Secondary indexesyesyesnoyes infosupports real-time indexing in full-text and geospatialyes
SQL infoSupport of SQLSQL for queryingyesSQL-like DML and DDL statementsYes, compatible with all major SQL variants through dedicated BI/SQL Serveryes infowith proprietary extensions
APIs and other access methodsJDBC
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
JDBC
ODBC
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C#
Java
PHP
Java
Python
R
Scala
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnoTransact SQLnouser defined functions and aggregates, HTTP Server extensions in Javayes infoproprietary syntax
Triggersnononoyes infovia event handlersyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedSharding, horizontal partitioningyes, utilizing Spark CorenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyesnoneMulti-source replication in HA-ClusterMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency in HA-ClusterEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsnoyes inforelationships in graphsyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemyesnoAccess rights for users and rolesUsers with fine-grained authorization concept infono user groups or roles

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More resources
Apache DruidMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSpark SQLStardogVitess
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