DBMS > Dgraph vs. Heroic vs. Oracle NoSQL vs. ReductStore

System Properties Comparison Dgraph vs. Heroic vs. Oracle NoSQL vs. ReductStore

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Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

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

Time Series DBMS

Document store
Key-value store
Relational 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	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Score	3.07
Rank	#86	Overall
	#15	Document stores
	#11	Key-value stores
	#47	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Website

dgraph.io

github.com/spotify/heroic

www.oracle.com/database/nosql/technologies/nosql

github.com/reductstore
www.reduct.store

Technical documentation

dgraph.io/docs

spotify.github.io/heroic

docs.oracle.com/en/database/other-databases/nosql-database/index.html

www.reduct.store/docs

Developer

Dgraph Labs, Inc.

Spotify

Oracle

ReductStore LLC

Initial release

2016

2014

2011

2023

Current release

24.1, May 2024

1.9, March 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

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

Java

C++, Rust

Server operating systems

Linux
OS X
Windows

Linux
Solaris SPARC/x86

Docker
Linux
macOS
Windows

Data scheme

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Typing

predefined data types such as float or date

yes

optional

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

via Elasticsearch

yes

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

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

HQL (Heroic Query Language, a JSON-based language)
HTTP API

RESTful HTTP API

HTTP API

Supported programming languages

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

C
C#
Go
Java
JavaScript (Node.js)
Python

C++
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

yes

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

Transaction concepts

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

ACID

configurable

ACID within a storage node (=shard)

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

off heap cache

User concepts

Access control

Planned for future releases

Access rights for users and roles

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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

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

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

provided by Google News

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13 December 2023, Channel Futures

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Top 8 Best NoSQL Databases in 2024
9 September 2024, AIM

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4 September 2018, Oracle

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20 July 2012, WIRED

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