DBMS > Amazon CloudSearch vs. Heroic vs. LevelDB vs. SQLite vs. Sqrrl

System Properties Comparison Amazon CloudSearch vs. Heroic vs. LevelDB vs. SQLite vs. Sqrrl

Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been 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

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Widely used embeddable, in-process RDBMS

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

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

Score	1.87
Rank	#140	Overall
	#12	Search engines

Score	0.57
Rank	#250	Overall
	#21	Time Series DBMS

Score	2.75
Rank	#107	Overall
	#19	Key-value stores

Score	116.01
Rank	#10	Overall
	#7	Relational DBMS

Website

aws.amazon.com/cloudsearch

github.com/spotify/heroic

github.com/google/leveldb

www.sqlite.org

sqrrl.com

Technical documentation

docs.aws.amazon.com/cloudsearch

spotify.github.io/heroic

github.com/google/leveldb/blob/main/doc/index.md

www.sqlite.org/docs.html

Developer

Amazon

Spotify

Google

Dwayne Richard Hipp

Amazon

originally Sqrrl Data, Inc.

Initial release

2012

2014

2011

2000

2012

Current release

1.23, February 2021

3.45.2 (12 March 2024), March 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

BSD

Open Source

Public Domain

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++

Java

Server operating systems

hosted

Illumos
Linux
OS X
Windows

server-less

Linux

Data scheme

yes

schema-free

yes

dynamic column types

schema-free

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.

Secondary indexes

yes

all search fields are automatically indexed

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

SQL-92 is not fully supported

APIs and other access methods

HTTP API

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

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

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

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

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

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

yes

none

selectable replication factor

making use of Hadoop

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

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic updates per row, document, or graph entity

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

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

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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