DBMS > AlaSQL vs. Google BigQuery vs. H2GIS vs. IBM Db2 Event Store

System Properties Comparison AlaSQL vs. Google BigQuery vs. H2GIS vs. IBM Db2 Event Store

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Large scale data warehouse service with append-only tables

Spatial extension of H2

Distributed Event Store optimized for Internet of Things use cases

Primary database model

Document store
Relational DBMS

Relational DBMS

Spatial DBMS

Event Store
Time Series DBMS

Secondary database models

Relational DBMS

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	52.67
Rank	#19	Overall
	#13	Relational DBMS

Score	0.00
Rank	#385	Overall
	#7	Spatial DBMS

Score	0.18
Rank	#315	Overall
	#2	Event Stores
	#26	Time Series DBMS

Website

alasql.org

cloud.google.com/bigquery

www.h2gis.org

www.ibm.com/products/db2-event-store

Technical documentation

github.com/AlaSQL/alasql

cloud.google.com/bigquery/docs

www.h2gis.org/docs/home

www.ibm.com/docs/en/db2-event-store

Developer

Andrey Gershun & Mathias R. Wulff

Google

CNRS

IBM

Initial release

2014

2010

2013

2017

Current release

2.0

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

LGPL 3.0

commercial

free developer edition 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

JavaScript

Java

C and C++

Server operating systems

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

hosted

Linux

Linux, macOS, Windows for the developer addition

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.

Secondary indexes

yes

SQL

Support of SQL

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

yes

through the embedded Spark runtime

APIs and other access methods

JavaScript API

RESTful HTTP/JSON API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

Supported programming languages

JavaScript

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Java

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

based on H2

yes

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

yes

based on H2

Active-active shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual 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

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

No - written data is immutable

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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)

yes

based on H2

fine grained access rights according to SQL-standard

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