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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. InterSystems IRIS Data platform vs Riak

InterSystems IRIS Data platform vs Riak

OverviewComparisonAlternatives

Overview

Riak
Riak
Stacks103
Followers137
Votes44
GitHub Stars4.0K
Forks535
InterSystems IRIS Data platform
InterSystems IRIS Data platform
Stacks11
Followers14
Votes0

InterSystems IRIS Data platform vs Riak: What are the differences?

InterSystems IRIS Data platform: Cloud-first data platform that includes a multi-model transactional data management engine, an application development platform, and interoperability engine, and an open analytics platform. It provides a set of APIs to operate with transactional persistent data simultaneously: key-value, relational, object, document, multidimensional Data can be managed by SQL, Java, node.js, .NET, C++, Python, and native server-side ObjectScript language.

It includes an Interoperability engine and modules to build AI solutions. It provides features for horizontal scalability (sharding, ECP) and provides High Availability features, Business intelligence, transaction support, and backup. ; Riak: A distributed, decentralized data storage system. Riak is a distributed database designed to deliver maximum data availability by distributing data across multiple servers. As long as your client can reach one Riak server, it should be able to write data. In most failure scenarios, the data you want to read should be available, although it may not be the most up-to-date version of that data.

InterSystems IRIS Data platform and Riak belong to "Databases" category of the tech stack.

Riak is an open source tool with 3.43K GitHub stars and 550 GitHub forks. Here's a link to Riak's open source repository on GitHub.

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Detailed Comparison

Riak
Riak
InterSystems IRIS Data platform
InterSystems IRIS Data platform

Riak is a distributed database designed to deliver maximum data availability by distributing data across multiple servers. As long as your client can reach one Riak server, it should be able to write data. In most failure scenarios, the data you want to read should be available, although it may not be the most up-to-date version of that data.

It provides a set of APIs to operate with transactional persistent data simultaneously: key-value, relational, object, document, multidimensional. Data can be managed by SQL, Java, node.js, .NET, C++, Python, and native server-side ObjectScript language. It includes an Interoperability engine and modules to build AI solutions. It provides features for horizontal scalability (sharding, ECP) and provides High Availability features, Business intelligence, transaction support, and backup.

-
Access Controls/Permissions; Data Dictionary Management; Data Replication; Database Conversion; Multiple Programming Languages Supported; Performance Analysis; Virtualization; Backup and Recovery; Data Migration; Data Storage Management; NOSQL; Relational
Statistics
GitHub Stars
4.0K
GitHub Stars
-
GitHub Forks
535
GitHub Forks
-
Stacks
103
Stacks
11
Followers
137
Followers
14
Votes
44
Votes
0
Pros & Cons
Pros
  • 14
    High Performance
  • 11
    High Availability
  • 9
    Easy Scalability
  • 5
    Flexible
  • 1
    Strong Consistency
No community feedback yet
Integrations
No integrations available
Node.js
Node.js
Java
Java
Python
Python
.NET
.NET
C++
C++

What are some alternatives to Riak, InterSystems IRIS Data platform?

MongoDB

MongoDB

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

MySQL

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

Microsoft SQL Server

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

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