DBMS > AlaSQL vs. etcd vs. HEAVY.AI vs. SQLite

System Properties Comparison AlaSQL vs. etcd vs. HEAVY.AI vs. SQLite

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Widely used embeddable, in-process RDBMS

Primary database model

Document store
Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Spatial 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	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

alasql.org

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

github.com/heavyai/heavydb
www.heavy.ai

www.sqlite.org

Technical documentation

github.com/AlaSQL/alasql

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

docs.heavy.ai

www.sqlite.org/docs.html

Developer

Andrey Gershun & Mathias R. Wulff

HEAVY.AI, Inc.

Dwayne Richard Hipp

Initial release

2014

2016

2000

Current release

3.4, August 2019

5.10, January 2022

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache Version 2.0

Open Source

Apache Version 2; enterprise edition available

Open Source

Public Domain

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

C++ and CUDA

Server operating systems

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

FreeBSD
Linux
Windows

experimental

Linux

server-less

Data scheme

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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.

yes

SQL-92 is not fully supported

APIs and other access methods

JavaScript API

gRPC
JSON over HTTP

JDBC
ODBC
Thrift
Vega

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

JavaScript

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

All languages supporting JDBC/ODBC/Thrift
Python

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

Server-side scripts

Stored procedures

Triggers

yes

yes, watching key changes

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

none

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.

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

via file-system locks

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

fine grained access rights according to SQL-standard

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