DBMS > Amazon Redshift vs. Axibase vs. GeoSpock vs. NCache vs. OrientDB

System Properties Comparison Amazon Redshift vs. Axibase vs. GeoSpock vs. NCache vs. OrientDB

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

Large scale data warehouse service for use with business intelligence tools

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

Spatial and temporal data processing engine for extreme data scale

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

Multi-model DBMS (Document, Graph, Key/Value)

Primary database model

Document store
Graph DBMS
Key-value store

Secondary database models

Time Series DBMS

Document store
Search engine

Using distributed Lucene

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.29
Rank	#292	Overall
	#25	Time Series DBMS

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

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Website

aws.amazon.com/redshift

axibase.com/docs/atsd/finance

geospock.com

www.alachisoft.com/ncache

orientdb.org

Technical documentation

docs.aws.amazon.com/redshift

www.alachisoft.com/resources/docs

www.orientdb.com/docs/last/index.html

Developer

Amazon (based on PostgreSQL)

Axibase Corporation

GeoSpock

Alachisoft

OrientDB LTD; CallidusCloud; SAP

Initial release

2012

2013

2005

2010

Current release

15585

2.0, September 2019

5.3.3, April 2024

3.2.29, March 2024

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

commercial

Open Source

Enterprise Edition available

Open Source

Apache version 2

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

Java, Javascript

C#, .NET, .NET Core, Java

Java

Server operating systems

hosted

Linux

hosted

Linux
Windows

All OS with a Java JDK (>= JDK 6)

Data scheme

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

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

restricted

temporal, categorical

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

ANSI SQL for query only (using Presto)

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

SQL-like query language, no joins

APIs and other access methods

JDBC
ODBC

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

JDBC

IDistributedCache
JCache
LINQ
Proprietary native API

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC

Go
Java
PHP
Python
R
Ruby

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

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

user defined functions

in Python

yes

support for stored procedures with SQL-Server CLR

Java, Javascript

Triggers

yes

Notifications

Hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic sharding

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes, with selectable consistency level

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

could be achieved with distributed queries

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

informational only, not enforced by the system

yes

relationship in graphs

Transaction concepts

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

ACID

optimistic locking and pessimistic locking

ACID

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

fine grained access rights according to SQL-standard

Access rights for users can be defined per table

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

Access rights for users and roles; record level security configurable

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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