DBMS > BigObject vs. Blueflood vs. Elasticsearch vs. EXASOL vs. NCache

System Properties Comparison BigObject vs. Blueflood vs. Elasticsearch vs. EXASOL vs. NCache

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Scalable TimeSeries DBMS based on Cassandra

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

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

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Document store
Search engine

Using distributed Lucene

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

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

Website

bigobject.io

blueflood.io

www.elastic.co/elasticsearch

www.exasol.com

www.alachisoft.com/ncache

Technical documentation

docs.bigobject.io

github.com/rax-maas/blueflood/wiki

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

www.exasol.com/resources

www.alachisoft.com/resources/docs

Developer

BigObject, Inc.

Rackspace

Elastic

Exasol

Alachisoft

Initial release

2015

2013

2010

2000

2005

Current release

8.6, January 2023

5.3.3, April 2024

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0

Open Source

Elastic License

commercial

Open Source

Enterprise Edition 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

Java

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

All OS with a Java VM

Linux
Windows

Data scheme

yes

predefined scheme

schema-free

Flexible type definitions. Once a type is defined, it is persistent

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

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

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

HTTP REST

Java API
RESTful HTTP/JSON API

.Net
JDBC
ODBC
WebSocket

IDistributedCache
JCache
LINQ
Proprietary native API

Supported programming languages

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

Java
Lua
Python
R

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

Server-side scripts

Stored procedures

Lua

yes

user defined functions

support for stored procedures with SQL-Server CLR

Triggers

yes

by using the 'percolation' feature

yes

Notifications

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

based on Cassandra

yes

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

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

Memcached and Redis integration

yes

User concepts

Access control

Access rights for users, groups and roles 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

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 ,...
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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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