DBMS > GridGain vs. Hyprcubd vs. NCache vs. Riak TS vs. SAP HANA

System Properties Comparison GridGain vs. Hyprcubd vs. NCache vs. Riak TS vs. SAP HANA

Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

GridGain is an in-memory computing platform, built on Apache Ignite

Serverless Time Series DBMS

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

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Key-value store
Relational DBMS

Secondary database models

Document store
Search engine

Using distributed Lucene

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

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

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

www.gridgain.com

hyprcubd.com (offline)

www.alachisoft.com/ncache

www.sap.com/products/hana.html

Technical documentation

www.gridgain.com/docs/index.html

www.alachisoft.com/resources/docs

www.tiot.jp/riak-docs/riak/ts/latest

help.sap.com/hana

Developer

GridGain Systems, Inc.

Hyprcubd, Inc.

Alachisoft

Open Source, formerly Basho Technologies

SAP

Initial release

2007

2005

2015

2010

Current release

GridGain 8.5.1

5.3.3, April 2024

3.0.0, September 2022

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

Enterprise Edition available

Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java, C++, .Net

C#, .NET, .NET Core, Java

Erlang

Server operating systems

Linux
OS X
Solaris
Windows

hosted

Linux
Windows

Linux
OS X

Appliance or cloud-service

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

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

restricted

yes

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

SQL-like query language

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

yes, limited

yes

APIs and other access methods

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

gRPC (https)

IDistributedCache
JCache
LINQ
Proprietary native API

HTTP API
Native Erlang Interface

JDBC
ODBC

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

support for stored procedures with SQL-Server CLR

Erlang

SQLScript, R

Triggers

yes (cache interceptors and events)

yes

Notifications

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

yes, with selectable consistency level

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between datasets can be stored

yes

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

Security Hooks for custom implementations

token access

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

yes

More information provided by the system vendor

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Market metrics

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Licensing and pricing models

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