DBMS > HyperSQL vs. NCache vs. TimescaleDB vs. TinkerGraph vs. XTDB

System Properties Comparison HyperSQL vs. NCache vs. TimescaleDB vs. TinkerGraph vs. XTDB

Editorial information provided by DB-Engines

Name

Description

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

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

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

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

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	0.94
Rank	#195	Overall
	#29	Key-value stores

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Score	0.08
Rank	#348	Overall
	#35	Graph DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

hsqldb.org

www.alachisoft.com/ncache

www.timescale.com

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

hsqldb.org/web/hsqlDocsFrame.html

www.alachisoft.com/resources/docs

docs.timescale.com

www.xtdb.com/docs

Developer

Alachisoft

Timescale

Juxt Ltd.

Initial release

2001

2005

2017

2009

2019

Current release

2.7.2, June 2023

5.3.3, April 2024

2.13.0, November 2023

1.19, September 2021

License

Commercial or Open Source

Open Source

based on BSD license

Open Source

Enterprise Edition available

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

MIT License

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C#, .NET, .NET Core, Java

Java

Clojure

Server operating systems

All OS with a Java VM

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

Linux
Windows

Linux
OS X
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

yes

schema-free

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

yes

yes, extensible-data-notation format

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

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

yes

full PostgreSQL SQL syntax

limited SQL, making use of Apache Calcite

APIs and other access methods

HTTP API

JDBC via HTTP
JDBC
ODBC

IDistributedCache
JCache
LINQ
Proprietary native API

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

TinkerPop 3

HTTP REST
JDBC

Supported programming languages

All languages supporting JDBC/ODBC
Java

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

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Groovy
Java

Clojure
Java

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

yes, across time and space (hash partitioning) attributes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, with selectable consistency level

Source-replica replication with hot standby and reads on replicas

none

yes, each node contains all data

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

none

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

optimistic locking and pessimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

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