DBMS > Amazon CloudSearch vs. BoltDB vs. Heroic vs. RocksDB vs. Splice Machine

System Properties Comparison Amazon CloudSearch vs. BoltDB vs. Heroic vs. RocksDB vs. Splice Machine

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

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

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

Primary database model

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

Score	1.87
Rank	#140	Overall
	#12	Search engines

Score	0.76
Rank	#224	Overall
	#32	Key-value stores

Score	0.57
Rank	#250	Overall
	#21	Time Series DBMS

Score	4.00
Rank	#84	Overall
	#11	Key-value stores

Score	0.54
Rank	#255	Overall
	#116	Relational DBMS

Website

aws.amazon.com/cloudsearch

github.com/boltdb/bolt

github.com/spotify/heroic

rocksdb.org

splicemachine.com

Technical documentation

docs.aws.amazon.com/cloudsearch

spotify.github.io/heroic

github.com/facebook/rocksdb/wiki

splicemachine.com/how-it-works

Developer

Amazon

Spotify

Facebook, Inc.

Splice Machine

Initial release

2012

2013

2014

2013

2014

Current release

8.11.4, April 2024

3.1, March 2021

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

Apache 2.0

Open Source

BSD

Open Source

AGPL 3.0, commercial license available

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++

Java

Server operating systems

hosted

BSD
Linux
OS X
Solaris
Windows

Linux

Linux
OS X
Solaris
Windows

Data scheme

yes

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

all search fields are automatically indexed

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

APIs and other access methods

HTTP API

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

C++ API
Java API

JDBC
Native Spark Datasource
ODBC

Supported programming languages

C
C++
Go
Java
Perl
Python
Ruby

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

Server-side scripts

Stored procedures

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

none

Sharding

horizontal partitioning

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

none

yes

Multi-source replication
Source-replica replication

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

none

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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 according to SQL-standard

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