DBMS > Amazon DocumentDB vs. Amazon Redshift vs. Elasticsearch vs. Hypertable vs. TimesTen

System Properties Comparison Amazon DocumentDB vs. Amazon Redshift vs. Elasticsearch vs. Hypertable vs. TimesTen

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

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

Large scale data warehouse service for use with business intelligence tools

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

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

In-Memory RDBMS compatible to Oracle

Primary database model

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

aws.amazon.com/documentdb

aws.amazon.com/redshift

www.elastic.co/elasticsearch

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

aws.amazon.com/documentdb/resources

docs.aws.amazon.com/redshift

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

docs.oracle.com/database/timesten-18.1

Developer

Amazon (based on PostgreSQL)

Elastic

Hypertable Inc.

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2019

2012

2010

2009

1998

Current release

8.6, January 2023

0.9.8.11, March 2016

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Open Source

Elastic License

Open Source

GNU version 3. Commercial license available

commercial

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++

Server operating systems

hosted

All OS with a Java VM

Linux
OS X
Windows

an inofficial Windows port is available

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

schema-free

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.

Secondary indexes

yes

restricted

yes

All search fields are automatically indexed

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

JDBC
ODBC

Java API
RESTful HTTP/JSON API

C++ API
Thrift

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

All languages supporting JDBC/ODBC

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

C++
Java
Perl
PHP
Python
Ruby

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

user defined functions

in Python

yes

PL/SQL

Triggers

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

yes

selectable replication factor on file system level

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

ES-Hadoop Connector

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

informational only, not enforced by the system

yes

Transaction concepts

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

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Memcached and Redis integration

yes

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

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