DBMS > Dgraph vs. EsgynDB vs. Graph Engine vs. LevelDB vs. ReductStore

System Properties Comparison Dgraph vs. EsgynDB vs. Graph Engine vs. LevelDB vs. ReductStore

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

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

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

Graph DBMS

Relational DBMS

Graph DBMS
Key-value store

Key-value store

Time Series DBMS

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

Score	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

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

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	0.05
Rank	#384	Overall
	#44	Time Series DBMS

Website

dgraph.io

www.esgyn.cn

www.graphengine.io

github.com/google/leveldb

github.com/reductstore
www.reduct.store

Technical documentation

dgraph.io/docs

www.graphengine.io/docs/manual

github.com/google/leveldb/blob/main/doc/index.md

www.reduct.store/docs

Developer

Dgraph Labs, Inc.

Esgyn

Microsoft

Google

ReductStore LLC

Initial release

2016

2015

2010

2011

2023

Current release

1.23, February 2021

1.9, March 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

MIT License

Open Source

BSD

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

C++, Java

.NET and C

C++

C++, Rust

Server operating systems

Linux
OS X
Windows

Linux

.NET

Illumos
Linux
OS X
Windows

Docker
Linux
macOS
Windows

Data scheme

schema-free

yes

schema-free

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

yes

APIs and other access methods

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

ADO.NET
JDBC
ODBC

RESTful HTTP API

HTTP API

Supported programming languages

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

All languages supporting JDBC/ODBC/ADO.Net

C#
C++
F#
Visual Basic

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C++
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

Multi-source replication between multi datacenters

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

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

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

yes

with automatic compression on writes

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

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

Dgraph Raises $6M in Seed Funding
20 July 2022, FinSMEs

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

Dgraph Rises to the Top Graph Database on GitHub With 11 G2 Badges and 11M Downloads
26 May 2021, Business Wire

provided by Google News

Trinity
30 October 2010, Microsoft

Open source Microsoft Graph Engine takes on Neo4j
13 February 2017, InfoWorld

IBM releases Graph, a service that can outperform SQL databases
27 July 2016, GeekWire

Aerospike Is Now a Graph Database, Too
21 June 2023, Datanami

The graph analytics landscape 2019 - DataScienceCentral.com
27 February 2019, Data Science Central

provided by Google News

Samstealer Attacking Windows Systems To Steal Sensitive Data
20 May 2024, CybersecurityNews

Pliops unveils XDP-Rocks for RocksDB – Blocks and Files
19 October 2022, Blocks and Files

Microsoft Teams stores auth tokens as cleartext in Windows, Linux, Macs
14 September 2022, BleepingComputer

XanMod, Liquorix Kernels Offer Some Advantages On AMD Ryzen 5 Notebook
26 July 2021, Phoronix

Threat Thursday: BlackGuard Infostealer Rises from Russian Underground Markets
21 April 2022, BlackBerry Blog

provided by Google News

Share this page