DBMS > AlaSQL vs. Google BigQuery vs. H2 vs. Riak TS vs. XTDB

System Properties Comparison AlaSQL vs. Google BigQuery vs. H2 vs. Riak TS vs. XTDB

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.

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Document store
Relational DBMS

Relational DBMS

Time Series DBMS

Document store

Secondary database models

Spatial 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	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

alasql.org

cloud.google.com/bigquery

www.h2database.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

github.com/AlaSQL/alasql

cloud.google.com/bigquery/docs

www.h2database.com/html/main.html

www.tiot.jp/riak-docs/riak/ts/latest

www.xtdb.com/docs

Developer

Andrey Gershun & Mathias R. Wulff

Google

Thomas Mueller

Open Source, formerly Basho Technologies

Juxt Ltd.

Initial release

2014

2010

2005

2015

2019

Current release

2.2.220, July 2023

3.0.0, September 2022

1.19, September 2021

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

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

Open Source

MIT License

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

JavaScript

Java

Erlang

Clojure

Server operating systems

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

hosted

All OS with a Java VM

Linux
OS X

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

restricted

yes

SQL

Support of SQL

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

yes

yes, limited

limited SQL, making use of Apache Calcite

APIs and other access methods

JavaScript API

RESTful HTTP/JSON API

JDBC
ODBC

HTTP API
Native Erlang Interface

HTTP REST
JDBC

Supported programming languages

JavaScript

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Java

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Clojure
Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Java Stored Procedures and User-Defined Functions

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

selectable replication factor

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

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)

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

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