DBMS > Amazon CloudSearch vs. BaseX vs. Google BigQuery vs. Quasardb vs. TimescaleDB

System Properties Comparison Amazon CloudSearch vs. BaseX vs. Google BigQuery vs. Quasardb vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

A hosted search engine service by Amazon with the data stored in Amazons cloud

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

Large scale data warehouse service with append-only tables

Distributed, high-performance timeseries database

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Secondary database models

Relational DBMS

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

Score	1.85
Rank	#137	Overall
	#12	Search engines

Score	1.73
Rank	#142	Overall
	#4	Native XML DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

aws.amazon.com/cloudsearch

basex.org

cloud.google.com/bigquery

quasar.ai

www.timescale.com

Technical documentation

docs.aws.amazon.com/cloudsearch

docs.basex.org

cloud.google.com/bigquery/docs

doc.quasar.ai/master

docs.timescale.com

Developer

Amazon

BaseX GmbH

Google

quasardb

Timescale

Initial release

2012

2007

2010

2009

2017

Current release

10.7, August 2023

3.14.1, January 2024

2.15.0, May 2024

License

Commercial or Open Source

commercial

Open Source

BSD license

commercial

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

Open Source

Apache 2.0

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

Java

C++

Server operating systems

hosted

Linux
OS X
Windows

hosted

BSD
Linux
OS X
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

XQuery supports types

yes

integer and binary

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

all search fields are automatically indexed

yes

with tags

yes

SQL

Support of SQL

yes

SQL-like query language

yes

full PostgreSQL SQL syntax

APIs and other access methods

HTTP API

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

RESTful HTTP/JSON API

HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

via events

yes

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

none

Sharding

consistent hashing

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

none

Source-replica replication with selectable replication factor

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

multiple readers, single writer

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

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

authentication via encrypted signatures

Users with fine-grained authorization concept on 4 levels

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

Google Cloud Identity & Access Management (IAM)

Cryptographically strong user authentication and audit trail

fine grained access rights according to SQL-standard

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