DBMS > Axibase vs. Dgraph vs. DolphinDB vs. Graph Engine

System Properties Comparison Axibase vs. Dgraph vs. DolphinDB vs. Graph Engine

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Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

Distributed and scalable native Graph DBMS

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

Primary database model

Time Series DBMS

Graph DBMS

Time Series DBMS

Graph DBMS
Key-value store

Secondary database models

Relational DBMS

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

Score	0.35
Rank	#282	Overall
	#25	Time Series DBMS

Score	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

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

Website

axibase.com/docs/atsd/finance

dgraph.io

www.dolphindb.com

www.graphengine.io

Technical documentation

dgraph.io/docs

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

www.graphengine.io/docs/manual

Developer

Axibase Corporation

Dgraph Labs, Inc.

DolphinDB, Inc

Microsoft

Initial release

2013

2016

2018

2010

Current release

15585

v2.00.4, January 2022

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

Open Source

Apache 2.0

commercial

free community version available

Open Source

MIT License

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

Java

C++

.NET and C

Server operating systems

Linux

Linux
OS X
Windows

Linux
Windows

.NET

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

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

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

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

RESTful HTTP API

Supported programming languages

Go
Java
PHP
Python
R
Ruby

C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

C#
C++
F#
Visual Basic

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Synchronous replication via Raft

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

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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.

yes

User concepts

Access control

Planned for future releases

Administrators, Users, Groups

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