DBMS > Alibaba Cloud AnalyticDB for MySQL vs. BigObject vs. Google BigQuery vs. Linter vs. Sphinx

System Properties Comparison Alibaba Cloud AnalyticDB for MySQL vs. BigObject vs. Google BigQuery vs. Linter vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

A real-time data warehousing service that can process petabytes of data with high concurrency and low latency. It is fully compatible with the MySQL protocol.

Analytic DBMS for real-time computations and queries

Large scale data warehouse service with append-only tables

RDBMS for high security requirements

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Search engine

Secondary database models

Document store

Spatial DBMS

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

Score	0.85
Rank	#207	Overall
	#96	Relational DBMS

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.09
Rank	#346	Overall
	#152	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

www.alibabacloud.com/product/analyticdb-for-mysql

bigobject.io

cloud.google.com/bigquery

linter.ru

sphinxsearch.com

Technical documentation

www.alibabacloud.com/help/doc-detail/93776.htm

docs.bigobject.io

cloud.google.com/bigquery/docs

sphinxsearch.com/docs

Developer

Alibaba

BigObject, Inc.

Google

relex.ru

Sphinx Technologies Inc.

Initial release

2015

2010

1990

2001

Current release

3.5.1, February 2023

License

Commercial or Open Source

commercial

free community edition available

commercial

Open Source

GPL version 2, commercial licence available

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

C and C++

C++

Server operating systems

hosted

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

hosted

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

Typing

predefined data types such as float or date

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

full-text index on all search fields

SQL

Support of SQL

yes

SQL-like DML and DDL statements

yes

SQL-like query language (SphinxQL)

APIs and other access methods

JDBC
ODBC

fluentd
ODBC
RESTful HTTP API

RESTful HTTP/JSON API

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

Proprietary protocol

Supported programming languages

C#
Java
PHP
Python

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

Lua

user defined functions

in JavaScript

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

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)

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

A real-time data warehousing service that can process PB data with high concurrency...
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Competitive advantages

TPC Benchmark: The world leading result in TPC-DS benchmark . TPC-H benchmark for...
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Licensing and pricing models

Available regions: America US Virginia US Silicon Valley Asia China Hong Kong India...
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