DBMS > AlaSQL vs. Google Cloud Bigtable vs. IBM Db2 warehouse vs. YottaDB

System Properties Comparison AlaSQL vs. Google Cloud Bigtable vs. IBM Db2 warehouse vs. YottaDB

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Cloud-based data warehousing service

A fast and solid embedded Key-value store

Primary database model

Document store
Relational DBMS

Key-value store
Wide column store

Relational DBMS

Key-value store

Secondary database models

Relational DBMS

using the Octo plugin

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

Score	0.42
Rank	#264	Overall
	#42	Document stores
	#122	Relational DBMS

Score	2.97
Rank	#92	Overall
	#15	Key-value stores
	#8	Wide column stores

Score	1.26
Rank	#162	Overall
	#73	Relational DBMS

Score	0.21
Rank	#309	Overall
	#43	Key-value stores

Website

alasql.org

cloud.google.com/bigtable

www.ibm.com/products/db2/warehouse

yottadb.com

Technical documentation

github.com/AlaSQL/alasql

cloud.google.com/bigtable/docs

yottadb.com/resources/documentation

Developer

Andrey Gershun & Mathias R. Wulff

Google

IBM

YottaDB, LLC

Initial release

2014

2015

2014

2001

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

AGPL 3.0

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

Docker
Linux

Data scheme

schema-free

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.

Import/export of XML data possible

Secondary indexes

yes

SQL

Support of SQL

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

yes

by using the Octo plugin

APIs and other access methods

JavaScript API

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

.NET Client API
JDBC
ODBC
OLE DB

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

JavaScript

C#
C++
Go
Java
JavaScript (Node.js)
Python

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

PL/SQL, SQL PL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Internal replication in Colossus, and regional replication between two clusters in different zones

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

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

Atomic single-row operations

ACID

optimistic locking

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 rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

Users and groups based on OS-security mechanisms

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