DBMS > AlaSQL vs. etcd vs. Hive vs. LeanXcale

System Properties Comparison AlaSQL vs. etcd vs. Hive vs. LeanXcale

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

A distributed reliable key-value store

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

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Primary database model

Document store
Relational DBMS

Key-value store

Relational DBMS

Key-value store
Relational DBMS

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

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

Score	7.25
Rank	#54	Overall
	#5	Key-value stores

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Website

alasql.org

etcd.io
github.com/etcd-io/etcd

hive.apache.org

www.leanxcale.com

Technical documentation

github.com/AlaSQL/alasql

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

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

Developer

Andrey Gershun & Mathias R. Wulff

Apache Software Foundation

initially developed by Facebook

LeanXcale

Initial release

2014

2012

2015

Current release

3.4, August 2019

3.1.3, April 2022

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache Version 2.0

Open Source

Apache Version 2

commercial

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

Server operating systems

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

FreeBSD
Linux
Windows

experimental

All OS with a Java VM

Data scheme

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

SQL

Support of SQL

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

SQL-like DML and DDL statements

yes

through Apache Derby

APIs and other access methods

JavaScript API

gRPC
JSON over HTTP

JDBC
ODBC
Thrift

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Supported programming languages

JavaScript

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

C++
Java
PHP
Python

C
Java
Scala

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Triggers

yes

yes, watching key changes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

selectable replication factor

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

none

Immediate Consistency

Eventual Consistency

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

ACID

Concurrency

Support for concurrent manipulation of data

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

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More resources

DB-Engines blog posts

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