DBMS > DolphinDB vs. GBase vs. ReductStore vs. Yaacomo

System Properties Comparison DolphinDB vs. GBase vs. ReductStore vs. Yaacomo

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Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed 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.

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Secondary database models

Relational DBMS

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

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	0.05
Rank	#384	Overall
	#44	Time Series DBMS

Website

www.dolphindb.com

www.gbase.cn

github.com/reductstore
www.reduct.store

yaacomo.com

Technical documentation

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

www.reduct.store/docs

Developer

DolphinDB, Inc

General Data Technology Co., Ltd.

ReductStore LLC

Q2WEB GmbH

Initial release

2018

2004

2023

2009

Current release

v2.00.4, January 2022

GBase 8a, GBase 8s, GBase 8c

1.9, March 2024

License

Commercial or Open Source

commercial

free community version available

commercial

Open Source

Business Source License 1.1

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C, Java, Python

C++, Rust

Server operating systems

Linux
Windows

Linux

Docker
Linux
macOS
Windows

Android
Linux
Windows

Data scheme

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

Standard with numerous extensions

yes

APIs and other access methods

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

ADO.NET
C API
JDBC
ODBC

HTTP API

JDBC
ODBC

Supported programming languages

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

C++
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

horizontal partitioning (by range, list and hash) and vertical partitioning

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

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

yes

Transaction concepts

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

yes

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

Administrators, Users, Groups

yes

fine grained access rights according to SQL-standard

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