DBMS > Dgraph vs. EsgynDB vs. MonetDB vs. Prometheus vs. TerarkDB

System Properties Comparison Dgraph vs. EsgynDB vs. MonetDB vs. Prometheus vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

A relational database management system that stores data in columns

Open-source Time Series DBMS and monitoring system

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

Secondary database models

Document store
Spatial DBMS

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

Score	1.39
Rank	#155	Overall
	#15	Graph DBMS

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	1.72
Rank	#135	Overall
	#62	Relational DBMS

Score	7.56
Rank	#49	Overall
	#3	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#61	Key-value stores

Website

github.com/bytedance/terarkdb

Technical documentation

dgraph.io/docs

www.monetdb.org/Documentation

prometheus.io/docs

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Dgraph Labs, Inc.

Esgyn

MonetDB BV

ByteDance, originally Terark

Initial release

2016

2015

2004

2015

2016

Current release

Dec2023 (11.49), December 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Mozilla Public License 2.0

Open Source

Apache 2.0

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++, Java

C++

Server operating systems

Linux
OS X
Windows

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data only

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.

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

SQL 2003 with some extensions

APIs and other access methods

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

ADO.NET
JDBC
ODBC

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

RESTful HTTP/JSON API

C++ API
Java API

Supported programming languages

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

All languages supporting JDBC/ODBC/ADO.Net

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

C++
Java

Server-side scripts

Stored procedures

Java Stored Procedures

yes, in SQL, C, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

Sharding via remote tables

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

Multi-source replication between multi datacenters

none

Source-replica replication available in experimental status

yes

by Federation

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

Planned for future releases

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Top Open Source Graph Databases
3 June 2024, MarkTechPost

Dgraph on AWS: Setting up a horizontally scalable graph database
1 September 2020, AWS Blog

Graph Database Market size to grow by USD 7.40 billion between 2022 - 2027 | Growth Driven by Lack of standardization and programming flexibility - Technavio
13 December 2023, Yahoo Finance

Dgraph raises $11.5 million for scalable graph database solutions
31 July 2019, VentureBeat

provided by Google News

MonetDB Foundation launched
31 January 2024, Centrum Wiskunde & Informatica (CWI)

PostgreSQL, MonetDB, and Too-Big-for-Memory Data in R — Part I
6 April 2018, Data Science Central

How MonetDB/X100 Exploits Modern CPU Performance
14 January 2020, Towards Data Science

Test of Time Award for paper on vectorized execution
16 January 2024, Centrum Wiskunde & Informatica (CWI)

Monet DB The Column-Store Pioneer
4 September 2019, Open Source For You

provided by Google News

Introducing the Amazon Timestream for LiveAnalytics Prometheus Connector
8 July 2024, AWS Blog

How to Monitor an Ubuntu Server With Prometheus: Collecting and Visualizing System Metrics
9 July 2024, Linux Journal

VTEX scales to 150 million metrics using Amazon Managed Service for Prometheus
10 March 2024, AWS Blog

Consider Grafana vs. Prometheus for your time-series tools
18 October 2021, TechTarget

My Prometheus is Overwhelmed! Help!
24 July 2021, hackernoon.com

provided by Google News

Share this page