DBMS > atoti vs. HarperDB vs. Kyligence Enterprise vs. NSDb

System Properties Comparison atoti vs. HarperDB vs. Kyligence Enterprise vs. NSDb

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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.

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

A distributed analytics engine for big data, built on top of Apache Kylin

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Primary database model

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Trend Chart

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	0.40
Rank	#269	Overall
	#124	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

atoti.io

www.harperdb.io

kyligence.io/kyligence-enterprise

nsdb.io

Technical documentation

docs.atoti.io

docs.harperdb.io/docs

nsdb.io/Architecture

Developer

ActiveViam

HarperDB

Kyligence, Inc.

Initial release

2017

2016

2017

Current release

3.1, August 2021

License

Commercial or Open Source

commercial

free versions available

commercial

free community edition available

commercial

Open Source

Apache Version 2.0

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

Node.js

Java

Java, Scala

Server operating systems

Linux
OS X

Linux

Linux
macOS

Data scheme

dynamic schema

yes

Typing

predefined data types such as float or date

yes

JSON data types

yes

yes: int, bigint, decimal, string

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

all fields are automatically indexed

SQL

Support of SQL

Multidimensional Expressions (MDX)

SQL-like data manipulation statements

ANSI SQL for queries (using Apache Calcite)

SQL-like query language

APIs and other access methods

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

JDBC
ODBC
RESTful HTTP API

gRPC
HTTP REST
WebSocket

Supported programming languages

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

Java
Scala

Server-side scripts

Stored procedures

Python

Custom Functions

since release 3.1

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

A table resides as a whole on one (or more) nodes in a cluster

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

the nodes on which a table resides can be defined

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of specific operations

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes, using LMDB

yes

Using Apache Lucene

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users and roles

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More resources

Recent citations in the news

Best use of cloud: ActiveViam
28 November 2023, Risk.net

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28 November 2023, Risk.net

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10 August 2021, VentureBeat

How Kyligence Cloud uses Amazon EMR Serverless to simplify OLAP | Amazon Web Services
9 November 2022, AWS Blog

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