DBMS > DolphinDB vs. Graph Engine vs. HarperDB vs. Memgraph vs. TerarkDB

System Properties Comparison DolphinDB vs. Graph Engine vs. HarperDB vs. Memgraph vs. TerarkDB

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.

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

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.

An open source graph database built for real-time streaming and compatible with Neo4j

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Time Series DBMS

Graph DBMS
Key-value store

Document store

Graph DBMS

Key-value store

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	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	3.02
Rank	#98	Overall
	#8	Graph DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

github.com/bytedance/terarkdb

Technical documentation

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

www.graphengine.io/docs/manual

docs.harperdb.io/docs

memgraph.com/docs

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Social network pages

Developer

DolphinDB, Inc

Microsoft

HarperDB

Memgraph Ltd

ByteDance, originally Terark

Initial release

2018

2010

2017

2016

Current release

v2.00.4, January 2022

3.1, August 2021

License

Commercial or Open Source

commercial

free community version available

Open Source

MIT License

commercial

free community edition available

Open Source

BSL 1.1; commercial license for enterprise edition available

commercial

restricted open source version available

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++

.NET and C

Node.js

C and C++

C++

Server operating systems

Linux
Windows

.NET

Linux
OS X

Linux

Data scheme

yes

dynamic schema

schema-free and schema-optional

schema-free

Typing

predefined data types such as float or date

yes

JSON data types

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

SQL-like data manipulation statements

APIs and other access methods

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

RESTful HTTP API

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

Bolt protocol
Cypher query language

C++ API
Java API

Supported programming languages

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

C#
C++
F#
Visual Basic

.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

.Net
C
C++
Elixir
Go
Haskell
Java
JavaScript
PHP
Python
Ruby
Scala

C++
Java

Server-side scripts

Stored procedures

yes

Custom Functions

since release 3.1

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

Sharding

dynamic graph partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

the nodes on which a table resides can be defined

Multi-source replication using RAFT

none

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

relationships in graphs

Transaction concepts

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

yes

Atomic execution of specific operations

ACID

with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

yes, using LMDB

yes

with periodic snapshot and write-ahead logging (WAL) of changes

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, roles and permissions

More information provided by the system vendor

Specific characteristics

Memgraph directly connects to your streaming infrastructure so you and your team...
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Competitive advantages

Business Source License ensures a future for the Memgraph community MAGE algorithm...
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Typical application scenarios

Graph algorithms in bioinformatics Social network analysis Cryptocurrency network...
» more

Licensing and pricing models

You can check out our pricing model and licenses on the company website .
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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