DBMS > HugeGraph vs. NCache vs. RavenDB vs. Spark SQL vs. Transbase

System Properties Comparison HugeGraph vs. NCache vs. RavenDB vs. Spark SQL vs. Transbase

Editorial information provided by DB-Engines

Name

Description

A fast-speed and highly-scalable Graph DBMS

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

Open Source Operational and Transactional Enterprise NoSQL Document Database

Spark SQL is a component on top of 'Spark Core' for structured data processing

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Secondary database models

Document store
Search engine

Using distributed Lucene

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

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

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

github.com/hugegraph
hugegraph.apache.org

www.alachisoft.com/ncache

ravendb.net

spark.apache.org/sql

www.transaction.de/en/products/transbase.html

Technical documentation

hugegraph.apache.org/docs

www.alachisoft.com/resources/docs

ravendb.net/docs

spark.apache.org/docs/latest/sql-programming-guide.html

www.transaction.de/en/products/transbase/features.html

Developer

Baidu

Alachisoft

Hibernating Rhinos

Apache Software Foundation

Transaction Software GmbH

Initial release

2018

2005

2010

2014

1987

Current release

0.9

5.3.3, April 2024

5.4, July 2022

3.5.0 ( 2.13), September 2023

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Enterprise Edition available

Open Source

AGPL version 3, commercial license available

Open Source

Apache 2.0

commercial

free development license

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

Scala

C and C++

Server operating systems

Linux
macOS
Unix

Linux
Windows

Linux
macOS
Raspberry Pi
Windows

Linux
OS X
Windows

FreeBSD
Linux
macOS
Solaris
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

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.

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

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

SQL-like query language (RQL)

SQL-like DML and DDL statements

yes

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

IDistributedCache
JCache
LINQ
Proprietary native API

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Groovy
Java
Python

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

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Java
Python
R
Scala

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

support for stored procedures with SQL-Server CLR

yes

Triggers

yes

Notifications

yes

Partitioning methods

Methods for storing different data on different nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

Sharding

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

yes, with selectable consistency level

Multi-source replication

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

ACID

optimistic locking and pessimistic locking

ACID, Cluster-wide transaction available

yes

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

Users, roles and permissions

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

Authorization levels configured per client per database

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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