DBMS > AlaSQL vs. Google BigQuery vs. H2 vs. HarperDB vs. MaxDB

System Properties Comparison AlaSQL vs. Google BigQuery vs. H2 vs. HarperDB vs. MaxDB

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Large scale data warehouse service with append-only tables

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

A robust and reliable RDBMS optimized to run all major SAP solutions

Primary database model

Document store
Relational DBMS

Relational DBMS

Document store

Relational DBMS

Secondary database models

Spatial 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	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	0.60
Rank	#244	Overall
	#38	Document stores

Score	2.26
Rank	#114	Overall
	#55	Relational DBMS

Website

alasql.org

cloud.google.com/bigquery

www.h2database.com

www.harperdb.io

maxdb.sap.com

Technical documentation

github.com/AlaSQL/alasql

cloud.google.com/bigquery/docs

www.h2database.com/html/main.html

docs.harperdb.io/docs

maxdb.sap.com/documentation

Developer

Andrey Gershun & Mathias R. Wulff

Google

Thomas Mueller

HarperDB

SAP, acquired from Software AG (Adabas-D) in 1997

Initial release

2014

2010

2005

2017

1984

Current release

2.2.220, July 2023

3.1, August 2021

7.9.10.12, February 2024

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

free community edition available

commercial

Limited community edition free

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

Node.js

C++

Server operating systems

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

hosted

All OS with a Java VM

Linux
OS X

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

yes

dynamic schema

yes

Typing

predefined data types such as float or date

yes

JSON data types

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

SQL-like data manipulation statements

yes

APIs and other access methods

JavaScript API

RESTful HTTP/JSON API

JDBC
ODBC

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

ADO.NET
JDBC
ODBC
WebDAV

Supported programming languages

JavaScript

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Java

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

.Net
C#
Java
Perl
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Java Stored Procedures and User-Defined Functions

Custom Functions

since release 3.1

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

A table resides as a whole on one (or more) nodes in a cluster

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

With clustering: 2 database servers on different computers operate on identical copies of a database

yes

the nodes on which a table resides can be defined

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

yes, using LMDB

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

fine grained access rights according to SQL-standard

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