DBMS > DolphinDB vs. HarperDB vs. RisingWave

System Properties Comparison DolphinDB vs. HarperDB vs. RisingWave

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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.

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

A distributed RDBMS for stream processing, wire-compatible with PostgreSQL

Primary database model

Time Series DBMS

Document store

Relational DBMS

Secondary database models

Relational DBMS

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

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	0.58
Rank	#242	Overall
	#111	Relational DBMS

Website

www.dolphindb.com

www.harperdb.io

www.risingwave.com/database

Technical documentation

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

docs.harperdb.io/docs

docs.risingwave.com/docs/current/intro

Developer

DolphinDB, Inc

HarperDB

RisingWave Labs

Initial release

2018

2017

2022

Current release

v2.00.4, January 2022

3.1, August 2021

1.2, September 2023

License

Commercial or Open Source

commercial

free community version available

commercial

free community edition available

Open Source

Apache Version 2.0

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++

Node.js

Rust

Server operating systems

Linux
Windows

Linux
OS X

Docker
Linux
macOS

Data scheme

yes

dynamic schema

yes

Typing

predefined data types such as float or date

yes

JSON data types

Standard SQL-types and JSON

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 data manipulation statements

yes

APIs and other access methods

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

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

JDBC
PostgreSQL wire protocol

Supported programming languages

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

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Custom Functions

since release 3.1

UDFs in Python or Java

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

A table resides as a whole on one (or more) nodes in a cluster

Replication methods

Methods for redundantly storing data on multiple nodes

yes

the nodes on which a table resides can be defined

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

Transaction concepts

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

yes

Atomic execution of specific operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

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 rights for users and roles

Users and Roles

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More resources

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