DBMS > Apache Doris vs. Apache Druid vs. LeanXcale vs. Microsoft Azure Synapse Analytics

System Properties Comparison Apache Doris vs. Apache Druid vs. LeanXcale vs. Microsoft Azure Synapse Analytics

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Editorial information provided by DB-Engines

Name

Description

An MPP-based analytics DBMS embracing the MySQL protocol

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

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

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

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Key-value store
Relational DBMS

Relational DBMS

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

Score	0.57
Rank	#244	Overall
	#113	Relational DBMS

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Website

doris.apache.org
github.com/apache/doris

druid.apache.org

www.leanxcale.com

azure.microsoft.com/services/synapse-analytics

Technical documentation

github.com/apache/doris/wiki

druid.apache.org/docs/latest/design

docs.microsoft.com/azure/synapse-analytics

Developer

Apache Software Foundation, originally contributed from Baidu

Apache Software Foundation and contributors

LeanXcale

Microsoft

Initial release

2017

2012

2015

2016

Current release

1.2.2, February 2023

29.0.1, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache license v2

commercial

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++

Server operating systems

Linux

Linux
OS X
Unix

hosted

Data scheme

yes

schema-less columns are supported

yes

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL for querying

yes

through Apache Derby

yes

APIs and other access methods

JDBC
MySQL client

JDBC
RESTful HTTP/JSON API

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

ADO.NET
JDBC
ODBC

Supported programming languages

Java

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C
Java
Scala

C#
Java
PHP

Server-side scripts

Stored procedures

user defined functions

Transact SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

manual/auto, time-based

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, via HDFS, S3 or other storage engines

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

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

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

fine grained access rights according to SQL-standard

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

yes

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