DBMS > Amazon CloudSearch vs. EXASOL vs. InfinityDB vs. Microsoft SQL Server vs. RRDtool

System Properties Comparison Amazon CloudSearch vs. EXASOL vs. InfinityDB vs. Microsoft SQL Server vs. RRDtool

Editorial information provided by DB-Engines

Name

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.

A Java embedded Key-Value Store which extends the Java Map interface

Microsofts flagship relational DBMS

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

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	1.87
Rank	#140	Overall
	#12	Search engines

Score	2.25
Rank	#120	Overall
	#57	Relational DBMS

Score	0.07
Rank	#359	Overall
	#54	Key-value stores

Score	829.80
Rank	#3	Overall
	#3	Relational DBMS

Score	2.14
Rank	#124	Overall
	#10	Time Series DBMS

Website

aws.amazon.com/cloudsearch

www.exasol.com

boilerbay.com

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

oss.oetiker.ch/rrdtool

Technical documentation

docs.aws.amazon.com/cloudsearch

www.exasol.com/resources

boilerbay.com/infinitydb/manual

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

oss.oetiker.ch/rrdtool/doc

Developer

Amazon

Exasol

Boiler Bay Inc.

Microsoft

Tobias Oetiker

Initial release

2012

2000

2002

1989

1999

Current release

4.0

SQL Server 2022, November 2022

1.8.0, 2022

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

GPL V2 and FLOSS

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++

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

hosted

All OS with a Java VM

Linux
Windows

HP-UX
Linux

Data scheme

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

yes

Numeric data only

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

Exporting into and restoring from XML files possible

Secondary indexes

yes

all search fields are automatically indexed

yes

manual creation possible, using inversions based on multi-value capability

yes

SQL

Support of SQL

yes

APIs and other access methods

HTTP API

.Net
JDBC
ODBC
WebSocket

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

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

in-process shared library
Pipes

Supported programming languages

Java
Lua
Python
R

Java

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

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

Sharding

none

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

none

yes, but depending on the SQL-Server Edition

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

READ-COMMITTED or SERIALIZED

Immediate Consistency

none

Foreign keys

Referential integrity

yes

manual creation possible, using inversions based on multi-value capability

yes

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

ACID

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

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

fine grained access rights according to SQL-standard

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