DBMS > AlaSQL vs. Google BigQuery vs. Microsoft Azure Table Storage vs. Quasardb vs. XTDB

System Properties Comparison AlaSQL vs. Google BigQuery vs. Microsoft Azure Table Storage vs. Quasardb vs. XTDB

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Large scale data warehouse service with append-only tables

A Wide Column Store for rapid development using massive semi-structured datasets

Distributed, high-performance timeseries database

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

Primary database model

Document store
Relational 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	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

alasql.org

cloud.google.com/bigquery

azure.microsoft.com/en-us/services/storage/tables

quasar.ai

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

Technical documentation

github.com/AlaSQL/alasql

cloud.google.com/bigquery/docs

doc.quasar.ai/master

www.xtdb.com/docs

Developer

Andrey Gershun & Mathias R. Wulff

Google

Microsoft

quasardb

Juxt Ltd.

Initial release

2014

2010

2012

2009

2019

Current release

3.14.1, January 2024

1.19, September 2021

License

Commercial or Open Source

Open Source

MIT-License

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

MIT 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

C++

Clojure

Server operating systems

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

hosted

BSD
Linux
OS X
Windows

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

integer and binary

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

with tags

yes

SQL

Support of SQL

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

yes

SQL-like query language

limited SQL, making use of Apache Calcite

APIs and other access methods

JavaScript API

RESTful HTTP/JSON API

RESTful HTTP API

HTTP API

HTTP REST
JDBC

Supported programming languages

JavaScript

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

Clojure
Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Source-replica replication with selectable replication factor

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

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

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

by using LevelDB

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

Transient mode

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

Access rights based on private key authentication or shared access signatures

Cryptographically strong user authentication and audit trail

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