DBMS > DolphinDB vs. EJDB vs. Spark SQL vs. Transbase vs. YottaDB

System Properties Comparison DolphinDB vs. EJDB vs. Spark SQL vs. Transbase vs. YottaDB

Editorial information provided by DB-Engines

Name

Description

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)

Spark SQL is a component on top of 'Spark Core' for structured data processing

A resource-optimized, high-performance, universally applicable RDBMS

A fast and solid embedded Key-value store

Primary database model

Secondary database models

Relational DBMS

using the Octo plugin

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

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Score	0.20
Rank	#317	Overall
	#47	Key-value stores

Website

www.dolphindb.com

github.com/Softmotions/ejdb

spark.apache.org/sql

www.transaction.de/en/products/transbase.html

yottadb.com

Technical documentation

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

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

spark.apache.org/docs/latest/sql-programming-guide.html

www.transaction.de/en/products/transbase/features.html

yottadb.com/resources/documentation

Developer

DolphinDB, Inc

Softmotions

Apache Software Foundation

Transaction Software GmbH

YottaDB, LLC

Initial release

2018

2012

2014

1987

2001

Current release

v2.00.4, January 2022

3.5.0 ( 2.13), September 2023

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

free community version available

Open Source

GPLv2

Open Source

Apache 2.0

commercial

free development license

Open Source

AGPL 3.0

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

C++

Scala

C and C++

Server operating systems

Linux
Windows

server-less

Linux
OS X
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Docker
Linux

Data scheme

yes

schema-free

yes

schema-free

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

SQL-like query language

SQL-like DML and DDL statements

yes

by using the Octo plugin

APIs and other access methods

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

in-process shared library

JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

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
Python
R
Scala

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

optimistic locking

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

Administrators, Users, Groups

fine grained access rights according to SQL-standard

Users and groups based on OS-security mechanisms

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