DBMS > Google BigQuery vs. GridGain vs. Kdb vs. SWC-DB

System Properties Comparison Google BigQuery vs. GridGain vs. Kdb vs. SWC-DB

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

GridGain is an in-memory computing platform, built on Apache Ignite

High performance Time Series DBMS

A high performance, scalable Wide Column DBMS

Primary database model

Relational DBMS

Columnar
Key-value store
Object oriented DBMS
Relational DBMS

Time Series DBMS
Vector DBMS

Wide column store

Secondary database models

Relational DBMS

Time Series DBMS

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

Score	52.67
Rank	#19	Overall
	#13	Relational DBMS

Score	1.48
Rank	#150	Overall
	#1	Columnar
	#26	Key-value stores
	#2	Object oriented DBMS
	#69	Relational DBMS

Score	7.73
Rank	#45	Overall
	#2	Time Series DBMS
	#1	Vector DBMS

Score	0.01
Rank	#378	Overall
	#13	Wide column stores

Website

cloud.google.com/bigquery

www.gridgain.com

kx.com

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

cloud.google.com/bigquery/docs

www.gridgain.com/docs/index.html

code.kx.com

Developer

Google

GridGain Systems, Inc.

Kx Systems, a division of First Derivatives plc

Alex Kashirin

Initial release

2010

2007

2000

kdb was released 2000, kdb+ in 2003

2020

Current release

GridGain 8.5.1

3.6, May 2018

0.5, April 2021

License

Commercial or Open Source

commercial

commercial, open source

commercial

free 32-bit version

Open Source

GPL V3

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

Java, C++, .Net, Python, REST, SQL

C++

Server operating systems

hosted

Linux
OS X
Solaris
Windows
z/OS

Linux
OS X
Solaris
Windows

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.

yes

Secondary indexes

yes

table attribute 'grouped'

SQL

Support of SQL

yes

ANSI-99 for query and DML statements, subset of DDL

SQL-like query language (q)

SQL-like query language

APIs and other access methods

RESTful HTTP/JSON API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

Proprietary protocol
Thrift

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala

C++

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes (compute grid and cache interceptors can be used instead)

user defined functions

Triggers

yes (cache interceptors and events)

yes

with views

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

similar paradigm used for internal processing

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

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

In-memory capabilities

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

yes

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

Role-based access control
Security Hooks for custom implementations

rights management via user accounts

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
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Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
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Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
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Key customers

Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more

Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
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Licensing and pricing models

upon request
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.