DBMS > AlaSQL vs. FeatureBase vs. Greenplum vs. Linter vs. Machbase Neo

System Properties Comparison AlaSQL vs. FeatureBase vs. Greenplum vs. Linter vs. Machbase Neo

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

RDBMS for high security requirements

TimeSeries DBMS for AIoT and BigData

Primary database model

Document store
Relational DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

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	0.31
Rank	#292	Overall
	#135	Relational DBMS

Score	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	0.12
Rank	#350	Overall
	#152	Relational DBMS

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Website

Technical documentation

github.com/AlaSQL/alasql

docs.featurebase.com

docs.greenplum.org

machbase.com/dbms

Developer

Andrey Gershun & Mathias R. Wulff

Molecula and Pilosa Open Source Contributors

Pivotal Software Inc.

relex.ru

Machbase

Initial release

2014

2017

2005

1990

2013

Current release

2022, May 2022

7.0.0, September 2023

V8.0, August 2023

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

Apache 2.0

commercial

free test version available

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 C++

Server operating systems

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

Linux
macOS

Linux

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Linux
macOS
Windows

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.

yes

since Version 4.2

Secondary indexes

yes

SQL

Support of SQL

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

SQL queries

yes

SQL-like query language

APIs and other access methods

JavaScript API

gRPC
JDBC
Kafka Connector
ODBC

JDBC
ODBC

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

Supported programming languages

JavaScript

Java
Python

C
Java
Perl
Python
R

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

Server-side scripts

Stored procedures

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Source-replica replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

yes

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, using Linux fsync

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

volatile and lookup table

User concepts

Access control

fine grained access rights according to SQL-standard

simple password-based access control

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

HarperDB - How and Why We Built It From The Ground Up on NodeJS
28 February 2021, hackernoon.com

Create a Marvel Database with SQL and Javascript, the easy way
2 July 2019, Towards Data Science

Multi faceted data exploration in the browser using Leaflet and amCharts
3 May 2020, Towards Data Science

provided by Google News

Get Your Infrastructure Ready for Real-Time Analytics
9 March 2022, Built In

Pilosa: A Scalable High Performance Bitmap Database Index
17 June 2019, hackernoon.com

The 10 Coolest Big Data Tools Of 2021
7 December 2021, CRN

32 Data and Analytics Startups That Will Go Big, According to VCs
28 September 2021, Business Insider

provided by Google News

1. Introducing the Greenplum Database - Data Warehousing with Greenplum [Book]
6 December 2018, oreilly.com

VMware Greenplum on AWS: Parallel Postgres for Enterprise Analytics at Scale | Amazon Web Services
9 September 2019, AWS Blog

RSA: EMC integrates Hadoop with Greenplum database
26 February 2013, DatacenterDynamics

Greenplum 6 ventures outside the analytic box | ZDNET
19 March 2019, ZDNet

Greenplum 6 review: Jack of all trades, master of some
7 November 2019, InfoWorld

provided by Google News

Share this page