DBMS > Apache Doris vs. DolphinDB vs. EJDB vs. EXASOL

System Properties Comparison Apache Doris vs. DolphinDB vs. EJDB vs. EXASOL

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

An MPP-based analytics DBMS embracing the MySQL protocol

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Primary database model

Secondary database models

Relational DBMS

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

Score	0.57
Rank	#244	Overall
	#113	Relational DBMS

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Website

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

www.dolphindb.com

github.com/Softmotions/ejdb

www.exasol.com

Technical documentation

github.com/apache/doris/wiki

docs.dolphindb.cn/en/help200/index.html

github.com/Softmotions/ejdb/blob/master/README.md

www.exasol.com/resources

Developer

Apache Software Foundation, originally contributed from Baidu

DolphinDB, Inc

Softmotions

Exasol

Initial release

2017

2018

2012

2000

Current release

1.2.2, February 2023

v2.00.4, January 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free community version available

Open Source

GPLv2

commercial

Cloud-based only

Only available as a cloud service

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
Windows

server-less

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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-like query language

yes

APIs and other access methods

JDBC
MySQL client

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

in-process shared library

.Net
JDBC
ODBC
WebSocket

Supported programming languages

Java

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

Java
Lua
Python
R

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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

Administrators, Users, Groups

Access rights for users, groups and roles according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Streamlining Data Operations: How a Grocery Chain Optimizes Workloads with Apache Doris
16 May 2024, hackernoon.com

Using Arrow Flight SQL Protocol in Apache Doris 2.1 For Super Fast Data Transfer
8 May 2024, hackernoon.com

How to Digest 15 Billion Logs Per Day and Keep Big Queries Within 1 Second
1 September 2023, KDnuggets

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Data Analytics: Apache Doris' Impact in Reporting, Tagging, and Data Lake Operations
8 January 2024, hackernoon.com

provided by Google News

Mathias Golombek, Chief Technology Officer of Exasol – Interview Series
21 May 2024, Unite.AI

Exasol Finds AI Underinvestment Leads to Business Failure, But Data Challenges Stall Rapid Adoption
14 May 2024, insideBIGDATA

It's Back to the Database Future for Exasol CEO Tewes
26 October 2023, Datanami

Exasol gets jolt of AI with Espresso suite of capabilities
26 February 2024, TechTarget

Exasol Unveils New Suite of AI Tools to Turbocharge Enterprise Data Analytics
21 February 2024, businesswire.com

provided by Google News

Share this page