DBMS > Apache Impala vs. Machbase Neo vs. Quasardb vs. STSdb

System Properties Comparison Apache Impala vs. Machbase Neo vs. Quasardb vs. STSdb

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

TimeSeries DBMS for AIoT and BigData

Distributed, high-performance timeseries database

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Relational DBMS

Time Series DBMS

Key-value store

Secondary database models

Document store

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

impala.apache.org

machbase.com

quasar.ai

github.com/STSSoft/STSdb4

Technical documentation

impala.apache.org/impala-docs.html

machbase.com/dbms

doc.quasar.ai/master

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Machbase

quasardb

STS Soft SC

Initial release

2013

2009

2011

Current release

4.1.0, June 2022

V8.0, August 2023

3.14.1, January 2024

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

free test version available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

GPLv2, commercial license 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

C++

Server operating systems

Linux

Linux
macOS
Windows

BSD
Linux
OS X
Windows

Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

integer and binary

yes

primitive types and user defined types (classes)

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

with tags

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

JDBC
ODBC

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

HTTP API

.NET Client API

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

C#
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication with selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

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

yes

Transient mode

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

simple password-based access control

Cryptographically strong user authentication and audit trail

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More resources

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