DBMS > Amazon CloudSearch vs. SAP HANA vs. Splice Machine vs. SQLite

System Properties Comparison Amazon CloudSearch vs. SAP HANA vs. Splice Machine vs. SQLite

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Editorial information provided by DB-Engines

Name

Description

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

In-memory, column based data store. Available as appliance or cloud service

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Widely used embeddable, in-process RDBMS

Primary database model

Search engine

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	1.81
Rank	#137	Overall
	#12	Search engines

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

aws.amazon.com/cloudsearch

www.sap.com/products/hana.html

splicemachine.com

www.sqlite.org

Technical documentation

docs.aws.amazon.com/cloudsearch

help.sap.com/hana

splicemachine.com/how-it-works

www.sqlite.org/docs.html

Developer

Amazon

SAP

Splice Machine

Dwayne Richard Hipp

Initial release

2012

2010

2014

2000

Current release

2.0 SPS07 (April 4, 2023), April 2023

3.1, March 2021

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Open Source

AGPL 3.0, commercial license available

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

hosted

Appliance or cloud-service

Linux
OS X
Solaris
Windows

server-less

Data scheme

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

all search fields are automatically indexed

yes

SQL

Support of SQL

yes

SQL-92 is not fully supported

APIs and other access methods

HTTP API

JDBC
ODBC

JDBC
Native Spark Datasource
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

SQLScript, R

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

yes

Shared Nothhing Auto-Sharding, Columnar Partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

yes

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark 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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

via file-system locks

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

yes

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

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