DBMS > atoti vs. Kdb vs. PieCloudDB

System Properties Comparison atoti vs. Kdb vs. PieCloudDB

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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.

High performance Time Series DBMS

A cloud-native analytic database platform with new technologoy for elastic MPP

Primary database model

Object oriented DBMS

Time Series DBMS
Vector DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.49
Rank	#244	Overall
	#11	Object oriented DBMS

Score	7.10
Rank	#48	Overall
	#2	Time Series DBMS
	#4	Vector DBMS

Score	0.19
Rank	#313	Overall
	#138	Relational DBMS

Website

atoti.io

kx.com

www.openpie.com

Technical documentation

docs.atoti.io

code.kx.com

Developer

ActiveViam

Kx Systems, a division of First Derivatives plc

OpenPie

Initial release

2000

kdb was released 2000, kdb+ in 2003

Current release

3.6, May 2018

2.1, January 2023

License

Commercial or Open Source

commercial

free versions available

commercial

free 32-bit version

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

Linux
OS X
Solaris
Windows

hosted

Data scheme

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

Secondary indexes

yes

table attribute 'grouped'

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

SQL-like query language (q)

yes

APIs and other access methods

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

CLI Client
JDBC
ODBC

Supported programming languages

C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala

Java
PL/SQL
Python
R

Server-side scripts

Stored procedures

Python

user defined functions

Triggers

yes

with views

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

similar paradigm used for internal processing

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

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

rights management via user accounts

User Roles and pluggable authentication with full SQL Standard

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