DBMS > HyperSQL vs. Kyligence Enterprise vs. NCache vs. RocksDB vs. TimescaleDB

System Properties Comparison HyperSQL vs. Kyligence Enterprise vs. NCache vs. RocksDB vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

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

Open-Source and Enterprise in-memory Key-Value Store

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Relational DBMS

Key-value store

Time Series DBMS

Secondary database models

Document store
Search engine

Using distributed Lucene

Relational DBMS

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

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	0.40
Rank	#269	Overall
	#124	Relational DBMS

Score	0.94
Rank	#195	Overall
	#29	Key-value stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

hsqldb.org

kyligence.io/kyligence-enterprise

www.alachisoft.com/ncache

rocksdb.org

www.timescale.com

Technical documentation

hsqldb.org/web/hsqlDocsFrame.html

www.alachisoft.com/resources/docs

github.com/facebook/rocksdb/wiki

docs.timescale.com

Developer

Kyligence, Inc.

Alachisoft

Facebook, Inc.

Timescale

Initial release

2001

2016

2005

2013

2017

Current release

2.7.2, June 2023

5.3.3, April 2024

8.11.4, April 2024

2.15.0, May 2024

License

Commercial or Open Source

Open Source

based on BSD license

commercial

Open Source

Enterprise Edition available

Open Source

BSD

Open Source

Apache 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

C#, .NET, .NET Core, Java

C++

Server operating systems

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux

Linux
Windows

Linux

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

SQL

Support of SQL

yes

ANSI SQL for queries (using Apache Calcite)

SQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

yes

full PostgreSQL SQL syntax

APIs and other access methods

HTTP API

JDBC via HTTP
JDBC
ODBC

JDBC
ODBC
RESTful HTTP API

IDistributedCache
JCache
LINQ
Proprietary native API

C++ API
Java API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

All languages supporting JDBC/ODBC
Java

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

C
C++
Go
Java
Perl
Python
Ruby

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

Java, SQL

support for stored procedures with SQL-Server CLR

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Notifications

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

horizontal partitioning

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, with selectable consistency level

yes

Source-replica replication with hot standby and reads on replicas

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
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking and pessimistic locking

yes

ACID

Concurrency

Support for concurrent manipulation of data

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

fine grained access rights according to SQL-standard

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

NCache has been the market leader in .NET Distributed Caching since 2005 . NCache...
» more

Competitive advantages

NCache is 100% .NET/ .NET Core based which fully supports ASP.NET Core Sessions ,...
» more

Typical application scenarios

NCache enables industries like retail, finance, banking IoT, travel, ecommerce, healthcare...
» more

Key customers

Bank of America, Citi, Natures Way, Charter Spectrum, Barclays, Henry Schein, GBM,...
» more

Market metrics

Market Leader in .NET Distributed Caching since 2005.
» more

Licensing and pricing models

NCache Open Source is free on an as-is basis without any support. NCache Enterprise...
» more

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.