DBMS > Alibaba Cloud Table Store vs. Datomic vs. MonetDB vs. NCache vs. RocksDB

System Properties Comparison Alibaba Cloud Table Store vs. Datomic vs. MonetDB vs. NCache vs. RocksDB

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

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

A relational database management system that stores data in columns

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

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

Primary database model

Wide column store

Relational DBMS

Key-value store

Secondary database models

Document store
Spatial DBMS

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	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

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

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

Website

www.alibabacloud.com/product/table-store

www.datomic.com

www.monetdb.org

www.alachisoft.com/ncache

rocksdb.org

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.datomic.com

www.monetdb.org/Documentation

www.alachisoft.com/resources/docs

github.com/facebook/rocksdb/wiki

Developer

Alibaba

Cognitect

MonetDB BV

Alachisoft

Facebook, Inc.

Initial release

2016

2012

2004

2005

2013

Current release

1.0.6735, June 2023

Dec2023 (11.49), December 2023

5.3.3, April 2024

8.11.4, April 2024

License

Commercial or Open Source

commercial

limited edition free

Open Source

Mozilla Public License 2.0

Open Source

Enterprise Edition available

Open Source

BSD

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

Java, Clojure

C#, .NET, .NET Core, Java

C++

Server operating systems

hosted

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Windows

Linux

Data scheme

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

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

SQL

Support of SQL

yes

SQL 2003 with some extensions

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

APIs and other access methods

HTTP API

RESTful HTTP API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

IDistributedCache
JCache
LINQ
Proprietary native API

C++ API
Java API

Supported programming languages

Java
Python

Clojure
Java

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

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

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Transaction Functions

yes, in SQL, C, R

support for stored procedures with SQL-Server CLR

Triggers

By using transaction functions

yes

Notifications

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

But extensive use of caching in the application peers

Sharding via remote tables

yes

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

But extensive use of caching in the application peers

none

Source-replica replication available in experimental status

yes, with selectable consistency level

yes

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

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

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

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)

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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