DBMS > AlaSQL vs. Google BigQuery vs. OushuDB vs. Splunk vs. Teradata

System Properties Comparison AlaSQL vs. Google BigQuery vs. OushuDB vs. Splunk vs. Teradata

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Large scale data warehouse service with append-only tables

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

Analytics Platform for Big Data

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Document store
Relational DBMS

Relational DBMS

Search engine

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.51
Rank	#256	Overall
	#40	Document stores
	#118	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.10
Rank	#355	Overall
	#154	Relational DBMS

Score	89.10
Rank	#14	Overall
	#2	Search engines

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Website

alasql.org

cloud.google.com/bigquery

www.oushu.com/product/oushuDB

www.splunk.com

www.teradata.com

Technical documentation

github.com/AlaSQL/alasql

cloud.google.com/bigquery/docs

www.oushu.com/documentation

docs.splunk.com/Documentation/Splunk

docs.teradata.com

Developer

Andrey Gershun & Mathias R. Wulff

Google

Oushu

Splunk Inc.

Teradata

Initial release

2014

2010

2003

1984

Current release

4.0.1, August 2020

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

MIT-License

commercial

Limited free edition and free developer edition available

commercial

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

JavaScript

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

hosted

Linux

Linux
OS X
Solaris
Windows

hosted
Linux

Data scheme

schema-free

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

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

Close to SQL99, but no user access control, stored procedures and host language bindings.

yes

Full-featured ANSI SQL support

Splunk Search Processing Language for search commands

yes

SQL 2016 + extensions

APIs and other access methods

JavaScript API

RESTful HTTP/JSON API

JDBC
ODBC

HTTP REST

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

JavaScript

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C++

C#
Java
JavaScript
PHP
Python
Ruby

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

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

by using IndexedDB, SQL.JS or proprietary FileStorage

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)

Kerberos, SSL and role based access

Access rights for users and roles

fine grained access rights according to SQL-standard

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