DBMS > atoti vs. HEAVY.AI vs. Quasardb vs. searchxml

System Properties Comparison atoti vs. HEAVY.AI vs. Quasardb vs. searchxml

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Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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

Distributed, high-performance timeseries database

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Object oriented DBMS

Relational DBMS

Time Series DBMS

Native XML DBMS
Search engine

Secondary database models

Spatial DBMS

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Website

atoti.io

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

quasar.ai

www.searchxml.net/category/products

Technical documentation

docs.atoti.io

docs.heavy.ai

doc.quasar.ai/master

www.searchxml.net/support/handouts

Developer

ActiveViam

HEAVY.AI, Inc.

quasardb

informationpartners gmbh

Initial release

2016

2009

2015

Current release

5.10, January 2022

3.14.1, January 2024

1.0

License

Commercial or Open Source

commercial

free versions available

Open Source

Apache Version 2; enterprise edition available

commercial

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

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

Java

C++ and CUDA

C++

Server operating systems

Linux

BSD
Linux
OS X
Windows

Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

integer and binary

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

Secondary indexes

yes

with tags

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC
Thrift
Vega

HTTP API

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

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

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

Python

yes

on the application server

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

Round robin

Sharding

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication with selectable replication factor

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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

Transient mode

User concepts

Access control

fine grained access rights according to SQL-standard

Cryptographically strong user authentication and audit trail

Domain, group and role-based access control at the document level and for application services

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