DBMS > AlaSQL vs. Hive vs. RethinkDB vs. Sqrrl vs. SwayDB

System Properties Comparison AlaSQL vs. Hive vs. RethinkDB vs. Sqrrl vs. SwayDB

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

JavaScript DBMS library

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

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Adaptable, secure NoSQL built on Apache Accumulo

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Document store
Relational DBMS

Relational DBMS

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Key-value store

Secondary database models

Spatial DBMS

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

Score	0.51
Rank	#256	Overall
	#40	Document stores
	#118	Relational DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	2.66
Rank	#107	Overall
	#20	Document stores

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Website

sqrrl.com

Technical documentation

github.com/AlaSQL/alasql

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

rethinkdb.com/docs

Developer

Andrey Gershun & Mathias R. Wulff

Apache Software Foundation

initially developed by Facebook

The Linux Foundation

since July 2017

Amazon

originally Sqrrl Data, Inc.

Simer Plaha

Initial release

2014

2012

2009

2012

2018

Current release

3.1.3, April 2022

2.4.1, August 2020

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache Version 2

Open Source

Apache Version 2

commercial

Open Source

GNU Affero GPL V3.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

JavaScript

Java

C++

Java

Scala

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

All OS with a Java VM

Linux
OS X
Windows

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

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

SQL

Support of SQL

Close to SQL99, but no user access control, stored procedures and host language bindings.

SQL-like DML and DDL statements

APIs and other access methods

JavaScript API

JDBC
ODBC
Thrift

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

JavaScript

C++
Java
PHP
Python

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Actionscript
C

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

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Triggers

yes

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

range based

Sharding

making use of Hadoop

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

Source-replica replication

selectable replication factor

making use of Hadoop

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Immediate Consistency

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

Atomic single-document operations

Atomic updates per row, document, or graph entity

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

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

Access rights for users, groups and roles

yes

users and table-level permissions

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

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