DBMS > BigObject vs. Couchbase vs. Linter vs. NCache vs. STSdb

System Properties Comparison BigObject vs. Couchbase vs. Linter vs. NCache vs. STSdb

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

RDBMS for high security requirements

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Document store

Relational DBMS

Key-value store

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

Spatial DBMS

Document store
Search engine

Using distributed Lucene

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

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	0.12
Rank	#350	Overall
	#152	Relational DBMS

Score	0.96
Rank	#195	Overall
	#29	Key-value stores

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

bigobject.io

www.couchbase.com

linter.ru

www.alachisoft.com/ncache

github.com/STSSoft/STSdb4

Technical documentation

docs.bigobject.io

docs.couchbase.com

www.alachisoft.com/resources/docs

Developer

BigObject, Inc.

Couchbase, Inc.

relex.ru

Alachisoft

STS Soft SC

Initial release

2015

2011

1990

2005

2011

Current release

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

5.3.3, April 2024

4.0.8, September 2015

License

Commercial or Open Source

commercial

free community edition available

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

commercial

Open Source

Enterprise Edition available

Open Source

GPLv2, commercial license available

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

C, C++, Go and Erlang

C and C++

C#, .NET, .NET Core, Java

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
OS X
Windows

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Linux
Windows

Windows

Data scheme

yes

schema-free

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

primitive types and user defined types (classes)

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

SQL-like DML and DDL statements

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

yes

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

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

IDistributedCache
JCache
LINQ
Proprietary native API

.NET Client API

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

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

C#
Java

Server-side scripts

Stored procedures

Lua

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

yes

proprietary syntax with the possibility to convert from PL/SQL

support for stored procedures with SQL-Server CLR

Triggers

yes

via the TAP protocol

yes

Notifications

Partitioning methods

Methods for storing different data on different nodes

none

Automatic Sharding

none

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

including cross data center replication
Source-replica replication

Source-replica replication

yes, with selectable consistency level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

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

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

optimistic locking and pessimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

Ephemeral buckets

yes

User concepts

Access control

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

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

Market Leader in .NET Distributed Caching since 2005.
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Licensing and pricing models

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