DBMS > Amazon CloudSearch vs. EXASOL vs. Google Cloud Datastore vs. Hypertable vs. Microsoft SQL Server

System Properties Comparison Amazon CloudSearch vs. EXASOL vs. Google Cloud Datastore vs. Hypertable vs. Microsoft SQL Server

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

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

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

An open source BigTable implementation based on distributed file systems such as Hadoop

Microsofts flagship relational DBMS

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	1.85
Rank	#137	Overall
	#12	Search engines

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

aws.amazon.com/cloudsearch

www.exasol.com

cloud.google.com/datastore

www.microsoft.com/en-us/sql-server

Technical documentation

docs.aws.amazon.com/cloudsearch

www.exasol.com/resources

cloud.google.com/datastore/docs

learn.microsoft.com/en-US/sql/sql-server

Developer

Amazon

Exasol

Google

Hypertable Inc.

Microsoft

Initial release

2012

2000

2008

2009

1989

Current release

0.9.8.11, March 2016

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Open Source

GNU version 3. Commercial license available

commercial

restricted free version is 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++

Server operating systems

hosted

Linux
OS X
Windows

an inofficial Windows port is available

Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, details here

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

all search fields are automatically indexed

yes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

yes

SQL-like query language (GQL)

yes

APIs and other access methods

HTTP API

.Net
JDBC
ODBC
WebSocket

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

C++ API
Thrift

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

Java
Lua
Python
R

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C++
Java
Perl
PHP
Python
Ruby

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Server-side scripts

Stored procedures

user defined functions

using Google App Engine

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

Multi-source replication using Paxos

selectable replication factor on file system level

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

yes

using Google Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

authentication via encrypted signatures

Access rights for users, groups and roles according to SQL-standard

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

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