DBMS > AlaSQL vs. Derby vs. Google BigQuery vs. HarperDB vs. Transbase

System Properties Comparison AlaSQL vs. Derby vs. Google BigQuery vs. HarperDB vs. Transbase

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

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

Large scale data warehouse service with append-only tables

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 resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Document store
Relational DBMS

Relational DBMS

Document store

Relational DBMS

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

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

Score	4.71
Rank	#69	Overall
	#37	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

alasql.org

db.apache.org/derby

cloud.google.com/bigquery

www.harperdb.io

www.transaction.de/en/products/transbase.html

Technical documentation

github.com/AlaSQL/alasql

db.apache.org/derby/manuals/index.html

cloud.google.com/bigquery/docs

docs.harperdb.io/docs

www.transaction.de/en/products/transbase/features.html

Developer

Andrey Gershun & Mathias R. Wulff

Apache Software Foundation

Google

HarperDB

Transaction Software GmbH

Initial release

2014

1997

2010

2017

1987

Current release

10.17.1.0, November 2023

3.1, August 2021

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache version 2

commercial

free community edition available

commercial

free development license

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 and C++

Server operating systems

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

All OS with a Java VM

hosted

Linux
OS X

FreeBSD
Linux
macOS
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.

yes

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

JDBC

RESTful HTTP/JSON API

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

JavaScript

Java

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.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

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

in JavaScript

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

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

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

ACID

Since BigQuery is designed for querying data

Atomic execution of specific operations

yes

Concurrency

Support for concurrent manipulation of data

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

fine grained access rights according to SQL-standard

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Access rights for users and roles

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.