DBMS > Amazon CloudSearch vs. GridGain vs. SAP Adaptive Server vs. SQLite vs. Typesense

System Properties Comparison Amazon CloudSearch vs. GridGain vs. SAP Adaptive Server vs. SQLite vs. Typesense

Editorial information provided by DB-Engines

Name

Description

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

GridGain is an in-memory computing platform, built on Apache Ignite

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

Widely used embeddable, in-process RDBMS

A typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity

Primary database model

Search engine

Key-value store
Relational DBMS

Relational DBMS

Search engine

Secondary database models

Spatial DBMS

with Boeing's Spatial Query Server

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

Score	1.85
Rank	#137	Overall
	#12	Search engines

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	36.31
Rank	#25	Overall
	#17	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	0.79
Rank	#210	Overall
	#14	Search engines

Website

aws.amazon.com/cloudsearch

www.gridgain.com

www.sap.com/products/technology-platform/sybase-ase.html

www.sqlite.org

typesense.org

Technical documentation

docs.aws.amazon.com/cloudsearch

www.gridgain.com/docs/index.html

help.sap.com/docs/SAP_ASE

www.sqlite.org/docs.html

typesense.org/docs

Developer

Amazon

GridGain Systems, Inc.

SAP, Sybase

Dwayne Richard Hipp

Initial release

2012

2007

1987

2000

2015

Current release

GridGain 8.5.1

16.0

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

commercial

Open Source

Public Domain

Open Source

GPL V3

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++, .Net

C and C++

C++

Server operating systems

hosted

Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Unix
Windows

server-less

Linux

Data scheme

yes

dynamic column types

schema-free

pre-defined schema optional

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

yes

SQL-92 is not fully supported

APIs and other access methods

HTTP API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

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

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

RESTful HTTP API

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

C
C++
Cobol
Java
Java
Perl
PHP
Python

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

.Net

community maintained
Clojure

community maintained
Dart

community maintained
Go

community maintained
Java

community maintained
JavaScript
Perl

community maintained
PHP
Python
Ruby
Rust

community maintained
Swift

community maintained

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

Java and Transact-SQL

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

yes (replicated cache)

Multi-source replication
Source-replica replication

none

Multi-source replication using RAFT

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

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

via file-system locks

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

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

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