DBMS > Dgraph vs. Google BigQuery vs. Kinetica vs. LokiJS vs. Oracle Coherence

System Properties Comparison Dgraph vs. Google BigQuery vs. Kinetica vs. LokiJS vs. Oracle Coherence

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

Large scale data warehouse service with append-only tables

Fully vectorized database across both GPUs and CPUs

In-memory JavaScript DBMS

Oracles in-memory data grid solution

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	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	0.43
Rank	#264	Overall
	#42	Document stores

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

Website

dgraph.io

cloud.google.com/bigquery

www.kinetica.com

github.com/techfort/LokiJS

www.oracle.com/java/coherence

Technical documentation

dgraph.io/docs

cloud.google.com/bigquery/docs

docs.kinetica.com

techfort.github.io/LokiJS

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

Developer

Dgraph Labs, Inc.

Google

Kinetica

Oracle

Initial release

2016

2010

2012

2014

2007

Current release

7.1, August 2021

14.1, August 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++

JavaScript

Java

Server operating systems

Linux
OS X
Windows

hosted

Linux

server-less, requires a JavaScript environment (browser, Node.js)

All OS with a Java VM

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

via views

SQL

Support of SQL

yes

SQL-like DML and DDL statements

APIs and other access methods

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

RESTful HTTP/JSON API

JDBC
ODBC
RESTful HTTP API

JavaScript API

JCache
JPA
RESTful HTTP API

Supported programming languages

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C++
Java
JavaScript (Node.js)
Python

JavaScript

.Net
C++
Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

user defined functions

View functions in JavaScript

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

none

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

Source-replica replication

none

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

none

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

atomic operations within a single collection possible

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

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 privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Access rights for users and roles on table level

authentification to access the cache via certificates or http basic authentication

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