DBMS > Apache Drill vs. BigchainDB vs. DolphinDB vs. Graph Engine vs. ReductStore

System Properties Comparison Apache Drill vs. BigchainDB vs. DolphinDB vs. Graph Engine vs. ReductStore

Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

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.

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

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.

Primary database model

Document store
Relational DBMS

Document store

Time Series DBMS

Graph DBMS
Key-value store

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	2.02
Rank	#124	Overall
	#22	Document stores
	#59	Relational DBMS

Score	0.85
Rank	#208	Overall
	#35	Document stores

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	0.05
Rank	#384	Overall
	#44	Time Series DBMS

Website

github.com/reductstore
www.reduct.store

Technical documentation

drill.apache.org/docs

bigchaindb.readthedocs.io/en/latest

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

www.graphengine.io/docs/manual

www.reduct.store/docs

Developer

Apache Software Foundation

DolphinDB, Inc

Microsoft

ReductStore LLC

Initial release

2012

2016

2018

2010

2023

Current release

1.20.3, January 2023

v2.00.4, January 2022

1.9, March 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

AGPL v3

commercial

free community version available

Open Source

MIT License

Open Source

Business Source License 1.1

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

Python

C++

.NET and C

C++, Rust

Server operating systems

Linux
OS X
Windows

Linux

Linux
Windows

.NET

Docker
Linux
macOS
Windows

Data scheme

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

SQL-like query language

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

CLI Client
RESTful HTTP API

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

RESTful HTTP API

HTTP API

Supported programming languages

C++

Go
Haskell
Java
JavaScript
Python
Ruby

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

C#
C++
F#
Visual Basic

C++
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes,with MongoDB ord RethinkDB

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

yes

Administrators, Users, Groups

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