DBMS > Apache Druid vs. Microsoft Azure Synapse Analytics vs. Stardog

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

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Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Graph DBMS
RDF store

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	2.49
Rank	#125	Overall
	#62	Relational DBMS
	#8	Time Series DBMS

Score	21.78
Rank	#34	Overall
	#20	Relational DBMS

Score	1.63
Rank	#163	Overall
	#14	Graph DBMS
	#6	RDF stores

Website

druid.apache.org

azure.microsoft.com/services/synapse-analytics

www.stardog.com

Technical documentation

druid.apache.org/docs/latest/design

docs.microsoft.com/azure/synapse-analytics

docs.stardog.com

Developer

Apache Software Foundation and contributors

Microsoft

Stardog-Union

Initial release

2012

2016

2010

Current release

25.0.0, January 2023

7.3.0, May 2020

License

Commercial or Open Source

Open Source

Apache license v2

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

Java

Server operating systems

Linux
OS X
Unix

hosted

Linux
macOS
Windows

Data scheme

yes

schema-less columns are supported

yes

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

SQL for querying

yes

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

JDBC
RESTful HTTP/JSON API

ADO.NET
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

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C#
Java
PHP

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

Transact SQL

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

relationships in graphs

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

yes

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

Stardog is an Enterprise Knowledge Graph platform, uniquely combining graph storage...
» more

Competitive advantages

Stardog provides a full featureset to aid in data integration for your complex data....
» more

Typical application scenarios

Stardog is frequently used for: Supply chain optimization Operational Risk Digital...
» more

Key customers

Bosch, NASA, Boehringer Ingelheim, Cisco, Schneider Electric, FINRA and more — https://www.stardog.com/customers/
» more

Market metrics

Stardog's technology is based on ground-breaking research by our founders cited 10,000+...
» more

Licensing and pricing models

You can start for free! It’s easy to get started using Stardog’s leading Enterprise...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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