DBMS > Dgraph vs. EsgynDB vs. HarperDB vs. Tigris

System Properties Comparison Dgraph vs. EsgynDB vs. HarperDB vs. Tigris

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Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

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

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.

A horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure

Primary database model

Graph DBMS

Relational DBMS

Document store

Document store
Key-value store
Search engine
Time Series DBMS

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

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	0.02
Rank	#369	Overall
	#51	Document stores
	#55	Key-value stores
	#24	Search engines
	#38	Time Series DBMS

Website

Technical documentation

dgraph.io/docs

docs.harperdb.io/docs

www.tigrisdata.com/docs

Developer

Dgraph Labs, Inc.

Esgyn

HarperDB

Tigris Data, Inc.

Initial release

2016

2015

2017

2022

Current release

3.1, August 2021

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free community edition available

Open Source

Apache Version 2.0

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

Node.js

Server operating systems

Linux
OS X
Windows

Linux

Linux
OS X

Linux
macOS
Windows

Data scheme

schema-free

yes

dynamic schema

yes

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

yes

SQL-like data manipulation statements

APIs and other access methods

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

ADO.NET
JDBC
ODBC

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

CLI Client
gRPC
RESTful HTTP API

Supported programming languages

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

All languages supporting JDBC/ODBC/ADO.Net

.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

Go
Java
JavaScript (Node.js)

Server-side scripts

Stored procedures

Java Stored Procedures

Custom Functions

since release 3.1

Triggers

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

A table resides as a whole on one (or more) nodes in a cluster

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

Multi-source replication between multi datacenters

yes

the nodes on which a table resides can be defined

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

yes

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

yes, using FoundationDB

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

Access rights for users and roles

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More resources

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