DBMS > DolphinDB vs. HBase vs. JSqlDb vs. SWC-DB

System Properties Comparison DolphinDB vs. HBase vs. JSqlDb vs. SWC-DB

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Editorial information provided by DB-Engines

Name

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

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.

Wide-column store based on Apache Hadoop and on concepts of BigTable

JavaScript Query Language Database, stores JavaScript objects and primitives

A high performance, scalable Wide Column DBMS

Primary database model

Time Series DBMS

Wide column store

Document store
Object oriented DBMS

Wide column store

Secondary database models

Relational DBMS

Time Series DBMS

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

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

www.dolphindb.com

hbase.apache.org

jsqldb.org (offline)

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

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

hbase.apache.org/book.html

Developer

DolphinDB, Inc

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Konrad von Backstrom

Alex Kashirin

Initial release

2018

2008

2018

2020

Current release

v2.00.4, January 2022

2.3.4, January 2021

0.8, December 2018

0.5, April 2021

License

Commercial or Open Source

commercial

free community version available

Open Source

Apache version 2

Open Source

GPL V3

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++

Java

C++

Server operating systems

Linux
Windows

Linux
Unix
Windows

using Cygwin

Linux
macOS
Windows

Linux

Data scheme

yes

schema-free, schema definition possible

schema-free

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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

APIs and other access methods

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

Java API
RESTful HTTP API
Thrift

Proprietary protocol
Thrift

Supported programming languages

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

C
C#
C++
Groovy
Java
PHP
Python
Scala

JavaScript

C++

Server-side scripts

Stored procedures

yes

Coprocessors in Java

functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

Single row ACID (across millions of columns)

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using RocksDB

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

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

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