DBMS > Google BigQuery vs. IBM Db2 vs. Splunk vs. Vitess vs. WakandaDB

System Properties Comparison Google BigQuery vs. IBM Db2 vs. Splunk vs. Vitess 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

Analytics Platform for Big Data

Scalable, distributed, cloud-native DBMS, extending MySQL

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

Search engine

Relational DBMS

Object oriented DBMS

Secondary database models

Document store
RDF store

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

with Db2 Spatial Extender

Document store
Spatial DBMS

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	89.10
Rank	#14	Overall
	#2	Search engines

Score	0.88
Rank	#203	Overall
	#95	Relational DBMS

Score	0.10
Rank	#356	Overall
	#16	Object oriented DBMS

Website

cloud.google.com/bigquery

www.ibm.com/products/db2

www.splunk.com

vitess.io

wakanda.github.io

Technical documentation

cloud.google.com/bigquery/docs

www.ibm.com/docs/en/db2

docs.splunk.com/Documentation/Splunk

vitess.io/docs

wakanda.github.io/doc

Developer

Google

IBM

Splunk Inc.

The Linux Foundation, PlanetScale

Wakanda SAS

Initial release

2010

1983

host version

2003

2013

2012

Current release

12.1, October 2016

15.0.2, December 2022

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

free version is available

commercial

Limited free edition and free developer edition available

Open Source

Apache Version 2.0, commercial licenses 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++

C++, JavaScript

Server operating systems

hosted

AIX
HP-UX
Linux
Solaris
Windows
z/OS

Linux
OS X
Solaris
Windows

Docker
Linux
macOS

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

Splunk Search Processing Language for search commands

yes

with proprietary extensions

APIs and other access methods

RESTful HTTP/JSON API

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

HTTP REST

ADO.NET
JDBC
MySQL protocol
ODBC

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

C#
Java
JavaScript
PHP
Python
Ruby

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

JavaScript

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

proprietary syntax

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

only with Windows/Unix/Linux Version

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

with separate tools (MQ, InfoSphere)

Multi-source replication

Multi-source replication
Source-replica 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

Eventual Consistency across shards
Immediate Consistency within a shard

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

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 at shard level

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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)

fine grained access rights according to SQL-standard

Access rights for users and roles

Users with fine-grained authorization concept

no user groups or roles

yes

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