DBMS > Amazon CloudSearch vs. Heroic vs. Hypertable vs. XTDB vs. Yaacomo

System Properties Comparison Amazon CloudSearch vs. Heroic vs. Hypertable vs. XTDB vs. Yaacomo

Editorial information provided by DB-Engines

Name

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

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

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

A general purpose database with bitemporal SQL and Datalog and graph queries

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

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

Score	1.81
Rank	#137	Overall
	#12	Search engines

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

aws.amazon.com/cloudsearch

github.com/spotify/heroic

github.com/xtdb/xtdb
www.xtdb.com

yaacomo.com

Technical documentation

docs.aws.amazon.com/cloudsearch

spotify.github.io/heroic

www.xtdb.com/docs

Developer

Amazon

Spotify

Hypertable Inc.

Juxt Ltd.

Q2WEB GmbH

Initial release

2012

2014

2009

2019

2009

Current release

0.9.8.11, March 2016

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GNU version 3. Commercial license available

Open Source

MIT License

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++

Clojure

Server operating systems

hosted

Linux
OS X
Windows

an inofficial Windows port is available

All OS with a Java 8 (and higher) VM
Linux

Android
Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

all search fields are automatically indexed

yes

via Elasticsearch

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

limited SQL, making use of Apache Calcite

yes

APIs and other access methods

HTTP API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

C++ API
Thrift

HTTP REST
JDBC

JDBC
ODBC

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

Clojure
Java

Server-side scripts

Stored procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

yes

selectable replication factor on file system level

yes, each node contains all data

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

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

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Amazon - the rising star in the DBMS market
3 August 2015, Matthias Gelbmann

The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

show all

Recent citations in the news

Amazon CloudSearch – Start Searching in One Hour for Less Than $100 / Month | Amazon Web Services
12 April 2012, AWS Blog

Searching CloudTrail Logs Easily with Amazon CloudSearch | AWS Startups Blog
21 October 2014, AWS Blog

AWS, Microsoft and Google should retire these cloud services
2 June 2020, TechTarget

CloudSearch Update – Price Reduction, Hebrew & Japanese Support, Partitioning, CloudTrail | Amazon Web Services
19 November 2014, AWS Blog

Serverless Reference Architectures with AWS Lambda
10 May 2016, All Things Distributed

provided by Google News

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

provided by Google News

TimescaleDB goes distributed; implements ‘Chunking’ over ‘Sharding’ for scaling-out
22 August 2019, Packt Hub

SQL and TimescaleDB. This article takes a closer look into… | by Alibaba Cloud
31 July 2019, DataDrivenInvestor

Decorate your Windows XP with Hyperdesk
30 July 2008, CNET

The Collective: Customize Your Computer & Your Phone With Star Trek
18 March 2009, TrekMovie

5 Free NoSQL Database Certification Courses Online in 2024
31 January 2024, Analytics India Magazine

provided by Google News

Share this page