DBMS > Amazon CloudSearch vs. Heroic vs. Hive vs. RocksDB

System Properties Comparison Amazon CloudSearch vs. Heroic vs. Hive vs. RocksDB

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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

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

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

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

Score	1.85
Rank	#137	Overall
	#12	Search engines

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

aws.amazon.com/cloudsearch

github.com/spotify/heroic

hive.apache.org

rocksdb.org

Technical documentation

docs.aws.amazon.com/cloudsearch

spotify.github.io/heroic

cwiki.apache.org/confluence/display/Hive/Home

github.com/facebook/rocksdb/wiki

Developer

Amazon

Spotify

Apache Software Foundation

initially developed by Facebook

Facebook, Inc.

Initial release

2012

2014

2012

2013

Current release

3.1.3, April 2022

8.11.4, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2

Open Source

BSD

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

Data scheme

yes

schema-free

yes

schema-free

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

all search fields are automatically indexed

yes

via Elasticsearch

yes

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

HTTP API

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

JDBC
ODBC
Thrift

C++ API
Java API

Supported programming languages

C++
Java
PHP
Python

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Triggers

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

yes

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

Concurrency

Support for concurrent manipulation of data

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

Access rights for users, groups and roles

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