DBMS > Alibaba Cloud Table Store vs. Cubrid vs. NCache vs. Snowflake vs. Sphinx

System Properties Comparison Alibaba Cloud Table Store vs. Cubrid vs. NCache vs. Snowflake vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

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

Cloud-based data warehousing service for structured and semi-structured data

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Secondary database models

Document store
Search engine

Using distributed Lucene

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

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

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

www.alibabacloud.com/product/table-store

cubrid.com (korean)
cubrid.org (english)

www.alachisoft.com/ncache

www.snowflake.com

sphinxsearch.com

Technical documentation

www.alibabacloud.com/help/en/tablestore

cubrid.org/manuals

www.alachisoft.com/resources/docs

docs.snowflake.net/manuals/index.html

sphinxsearch.com/docs

Developer

Alibaba

CUBRID Corporation, CUBRID Foundation

Alachisoft

Snowflake Computing Inc.

Sphinx Technologies Inc.

Initial release

2016

2008

2005

2014

2001

Current release

11.0, January 2021

5.3.3, April 2024

3.5.1, February 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Enterprise Edition available

commercial

Open Source

GPL version 2, commercial licence available

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

C, C++, Java

C#, .NET, .NET Core, Java

C++

Server operating systems

hosted

Linux
Windows

hosted

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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.

yes

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

yes

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

yes

SQL-like query language (SphinxQL)

APIs and other access methods

HTTP API

ADO.NET
JDBC
ODBC
OLE DB

IDistributedCache
JCache
LINQ
Proprietary native API

CLI Client
JDBC
ODBC

Proprietary protocol

Supported programming languages

Java
Python

C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

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

JavaScript (Node.js)
Python

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

Java Stored Procedures

support for stored procedures with SQL-Server CLR

user defined functions

Triggers

yes

Notifications

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

yes

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Source-replica replication

yes, with selectable consistency level

yes

none

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

Atomic single-row operations

ACID

optimistic locking and pessimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

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 based on subaccounts and tokens

fine grained access rights according to SQL-standard

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

Users with fine-grained authorization concept, user roles and pluggable authentication

More information provided by the system vendor

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Typical application scenarios

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