DBMS > Google BigQuery vs. IBM Db2 vs. Spark SQL vs. Splunk vs. WakandaDB

System Properties Comparison Google BigQuery vs. IBM Db2 vs. Spark SQL vs. Splunk vs. WakandaDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Common in IBM host environments, 2 different versions for host and Windows/Linux

Spark SQL is a component on top of 'Spark Core' for structured data processing

Analytics Platform for Big Data

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Relational DBMS

Search engine

Object oriented DBMS

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	125.90
Rank	#9	Overall
	#6	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	89.10
Rank	#14	Overall
	#2	Search engines

Score	0.10
Rank	#356	Overall
	#16	Object oriented DBMS

Website

cloud.google.com/bigquery

www.ibm.com/products/db2

spark.apache.org/sql

www.splunk.com

wakanda.github.io

Technical documentation

cloud.google.com/bigquery/docs

www.ibm.com/docs/en/db2

spark.apache.org/docs/latest/sql-programming-guide.html

docs.splunk.com/Documentation/Splunk

wakanda.github.io/doc

Developer

Google

IBM

Apache Software Foundation

Splunk Inc.

Wakanda SAS

Initial release

2010

1983

host version

2014

2003

2012

Current release

12.1, October 2016

3.5.0 ( 2.13), September 2023

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

free version is available

Open Source

Apache 2.0

commercial

Limited free edition and free developer edition available

Open Source

AGPLv3, extended commercial license available

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 and C++

Scala

C++, JavaScript

Server operating systems

hosted

AIX
HP-UX
Linux
Solaris
Windows
z/OS

Linux
OS X
Windows

Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

yes

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

SQL

Support of SQL

yes

SQL-like DML and DDL statements

Splunk Search Processing Language for search commands

APIs and other access methods

RESTful HTTP/JSON API

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

JDBC
ODBC

HTTP REST

RESTful HTTP API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

Java
Python
R
Scala

C#
Java
JavaScript
PHP
Python
Ruby

JavaScript

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

only with Windows/Unix/Linux Version

yes, utilizing Spark Core

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

with separate tools (MQ, InfoSphere)

none

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

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.

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

Access rights for users and roles

yes

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