DBMS > Google BigQuery vs. jBASE vs. Kinetica vs. NebulaGraph

System Properties Comparison Google BigQuery vs. jBASE vs. Kinetica vs. NebulaGraph

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

A robust multi-value DBMS comprising development tools and middleware

Fully vectorized database across both GPUs and CPUs

A distributed, linear scalable, high perfomant Graph DBMS

Primary database model

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	2.14
Rank	#120	Overall
	#10	Graph DBMS

Website

cloud.google.com/bigquery

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

www.kinetica.com

github.com/vesoft-inc/nebula
www.nebula-graph.io

Technical documentation

cloud.google.com/bigquery/docs

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

docs.kinetica.com

docs.nebula-graph.io

Developer

Google

Rocket Software (formerly Zumasys)

Kinetica

Vesoft Inc.

Initial release

2010

1991

2012

2019

Current release

5.7

7.1, August 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0 + Common Clause 1.0

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++

C++

Server operating systems

hosted

AIX
Linux
Windows

Linux

Data scheme

yes

schema-free

yes

Strong typed schema

Typing

predefined data types such as float or date

yes

optional

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.

yes

Secondary indexes

yes

Nebula Graph internally uses the Key-Value store RocksDB for persistency. The vertices, edges, and their properties are stored as Key while their values are stored as Value. The primary indexes are per Key and secondary indexes are per Value.

SQL

Support of SQL

yes

Embedded SQL for jBASE in BASIC

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

JDBC
ODBC
RESTful HTTP API

Browser interface
console (shell)
Cypher Query Language
GO Object Graph Mapper
Java Object Graph Mapper
NGBatis

ORM framework for NebulaGraph and Spring-Boot
Proprietary native API
Python Object Graph Mapper
Query language nGQL

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
Basic
Jabbascript
Java

C++
Java
JavaScript (Node.js)
Python

.Net
C++
Go
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

user defined functions

Triggers

yes

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

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Causal Clustering using Raft protocol

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using RocksDB

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

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

Google Cloud Identity & Access Management (IAM)

Access rights can be defined down to the item level

Access rights for users and roles on table level

Role-based access control

More information provided by the system vendor

Specific characteristics

NebulaGraph is a truly distributed, linearly scalable, lightning-fast graph database,...
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Competitive advantages

NebulaGraph boasts the world's only graph database solution that is able to host...
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Typical application scenarios

Social networking Fraud detection Knowledge graph Data warehouse management Anti...
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Key customers

Companies from a variety of industries have implemented NebulaGraph Database in production,...
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Market metrics

At our very early stage, NebulaGraph has already received over 10,000 stars on GitHub...
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Licensing and pricing models

NebulaGraph is open source and free to use under Apache 2.0 license.
» more

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