DBMS > Dgraph vs. EsgynDB vs. HarperDB vs. OrigoDB vs. Riak TS

System Properties Comparison Dgraph vs. EsgynDB vs. HarperDB vs. OrigoDB vs. Riak TS

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

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

HarperDB takes the "stack" out of "tech stack" by combining an ultra-fast document-style data store, in-memory cache, real-time message broker, and your application components into a single distributed technology.

A fully ACID in-memory object graph database

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

Graph DBMS

Relational DBMS

Document store

Document store
Object oriented DBMS

Time Series 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	0.55
Rank	#243	Overall
	#38	Document stores

Score	0.00
Rank	#385	Overall
	#54	Document stores
	#21	Object oriented DBMS

Score	0.17
Rank	#318	Overall
	#27	Time Series DBMS

Website

Technical documentation

dgraph.io/docs

docs.harperdb.io/docs

origodb.com/docs

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Dgraph Labs, Inc.

Esgyn

HarperDB

Robert Friberg et al

Open Source, formerly Basho Technologies

Initial release

2016

2015

2017

2009

under the name LiveDB

2015

Current release

3.1, August 2021

3.0.0, September 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free community edition available

Open Source

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

Erlang

Server operating systems

Linux
OS X
Windows

Linux

Linux
OS X

Linux
Windows

Linux
OS X

Data scheme

schema-free

yes

dynamic schema

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON data types

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

restricted

SQL

Support of SQL

yes

SQL-like data manipulation statements

yes, limited

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

.NET Client API
HTTP API
LINQ

HTTP API
Native Erlang Interface

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

.Net

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

Java Stored Procedures

Custom Functions

since release 3.1

yes

Erlang

Triggers

yes

Domain Events

yes

pre-commit hooks and post-commit hooks

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

horizontal partitioning

client side managed; servers are not synchronized

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

Source-replica replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

depending on model

links between datasets can be stored

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

Write ahead log

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

Access rights for users and roles

Role based authorization

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