DBMS > Dgraph vs. Kinetica vs. Oracle Coherence vs. ReductStore

System Properties Comparison Dgraph vs. Kinetica vs. Oracle Coherence vs. ReductStore

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Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

Fully vectorized database across both GPUs and CPUs

Oracles in-memory data grid solution

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

Secondary database models

Spatial DBMS
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	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

dgraph.io

www.kinetica.com

www.oracle.com/java/coherence

github.com/reductstore
www.reduct.store

Technical documentation

dgraph.io/docs

docs.kinetica.com

docs.oracle.com/en/middleware/standalone/coherence

www.reduct.store/docs

Developer

Dgraph Labs, Inc.

Kinetica

Oracle

ReductStore LLC

Initial release

2016

2012

2007

2023

Current release

7.1, August 2021

14.1, August 2023

1.9, March 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

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, C++

Java

C++, Rust

Server operating systems

Linux
OS X
Windows

Linux

All OS with a Java VM

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

SQL-like DML and DDL statements

APIs and other access methods

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

JDBC
ODBC
RESTful HTTP API

JCache
JPA
RESTful HTTP API

HTTP API

Supported programming languages

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

C++
Java
JavaScript (Node.js)
Python

.Net
C++
Java

C++
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Live Events

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

Source-replica replication

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

GPU vRAM or System RAM

yes

User concepts

Access control

Planned for future releases

Access rights for users and roles on table level

authentification to access the cache via certificates or http basic authentication

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More resources

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