DBMS > Google BigQuery vs. H2GIS vs. Kinetica vs. TinkerGraph

System Properties Comparison Google BigQuery vs. H2GIS vs. Kinetica vs. TinkerGraph

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Spatial extension of H2

Fully vectorized database across both GPUs and CPUs

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Secondary database models

Relational DBMS

Spatial DBMS
Time Series DBMS

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

Score	61.90
Rank	#19	Overall
	#13	Relational DBMS

Score	0.05
Rank	#372	Overall
	#7	Spatial DBMS

Score	0.69
Rank	#234	Overall
	#107	Relational DBMS

Score	0.12
Rank	#344	Overall
	#34	Graph DBMS

Website

cloud.google.com/bigquery

www.h2gis.org

www.kinetica.com

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

cloud.google.com/bigquery/docs

www.h2gis.org/docs/home

docs.kinetica.com

Developer

Google

CNRS

Kinetica

Initial release

2010

2013

2012

2009

Current release

7.1, August 2021

License

Commercial or Open Source

commercial

Open Source

LGPL 3.0

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C, C++

Java

Server operating systems

hosted

Linux

Data scheme

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

yes

SQL-like DML and DDL statements

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC
RESTful HTTP API

TinkerPop 3

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Java

C++
Java
JavaScript (Node.js)
Python

Groovy
Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

based on H2

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on H2

Source-replica replication

none

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

none

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

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

optional

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)

yes

based on H2

Access rights for users and roles on table level

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