DBMS > AlaSQL vs. HEAVY.AI vs. Riak TS vs. Speedb vs. SQLite

System Properties Comparison AlaSQL vs. HEAVY.AI vs. Riak TS vs. Speedb vs. SQLite

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

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

An embeddable, high performance key-value store optimized for write-intensive workloads, which can be used as a drop-in replacement for RocksDB

Widely used embeddable, in-process RDBMS

Primary database model

Document 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	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Score	0.21
Rank	#315	Overall
	#45	Key-value stores

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

alasql.org

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

www.speedb.io

www.sqlite.org

Technical documentation

github.com/AlaSQL/alasql

docs.heavy.ai

www.tiot.jp/riak-docs/riak/ts/latest

www.sqlite.org/docs.html

Developer

Andrey Gershun & Mathias R. Wulff

HEAVY.AI, Inc.

Open Source, formerly Basho Technologies

Speedb

Dwayne Richard Hipp

Initial release

2014

2016

2015

2020

2000

Current release

5.10, January 2022

3.0.0, September 2022

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache Version 2.0; commercial license 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

Erlang

C++

Server operating systems

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

Linux

Linux
OS X

Linux
Windows

server-less

Data scheme

schema-free

yes

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

restricted

yes

SQL

Support of SQL

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

yes

yes, limited

yes

SQL-92 is not fully supported

APIs and other access methods

JavaScript API

JDBC
ODBC
Thrift
Vega

HTTP API
Native Erlang Interface

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

JavaScript

All languages supporting JDBC/ODBC/Thrift
Python

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C
C++
Go
Java
Perl
Python
Ruby

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

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

selectable replication factor

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

yes

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

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Licensing and pricing models

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