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KNIME VS Apache Cassandra

Compare KNIME VS Apache Cassandra and see what are their differences

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KNIME logo KNIME

KNIME, the open platform for your data.

Apache Cassandra logo Apache Cassandra

The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance.
  • KNIME Landing page
    Landing page //
    2023-09-28
  • Apache Cassandra Landing page
    Landing page //
    2022-04-17

KNIME features and specs

  • User-Friendly Interface
    KNIME provides a visual workflow interface that makes it easy for users to design data processing, analysis, and machine learning workflows without needing to write code.
  • Extensibility
    KNIME supports various extensions and plugins, which enhance its functionality and allow integration with different data sources, tools, and programming languages like R and Python.
  • Open Source
    KNIME offers an open-source platform, which means users can access and modify the source code, contributing to its flexibility and cost-effectiveness.
  • Robust Community Support
    A strong community of users and developers around KNIME provides extensive documentation, forums, and shared workflows to help solve issues and improve the platform.
  • Scalability
    KNIME can handle large volumes of data and complex workflows, making it scalable for both small projects and large enterprise solutions.

Possible disadvantages of KNIME

  • Learning Curve
    While the interface is user-friendly, new users may initially find it challenging to understand all the features and capabilities, leading to a significant learning curve.
  • Performance
    For extremely large datasets or very complex workflows, KNIME can exhibit performance issues, including slower processing speeds and higher memory consumption.
  • Limited Advanced Machine Learning Capabilities
    While KNIME is powerful for basic and intermediate analytics, it may lack some of the advanced machine learning capabilities found in specialized tools like TensorFlow or PyTorch.
  • Dependency on Extensions
    A lot of KNIME’s advanced functionality relies on external extensions, which may not always be well-maintained or compatible with newer versions.
  • Commercial Licensing Costs
    While the core platform is open-source, advanced features, support, and enterprise-level tools require a commercial license, which can be costly.

Apache Cassandra features and specs

  • Scalability
    Apache Cassandra is designed for linear scalability and can handle large volumes of data across many commodity servers without a single point of failure.
  • High Availability
    Cassandra ensures high availability by replicating data across multiple nodes. Even if some nodes fail, the system remains operational.
  • Performance
    It provides fast writes and reads by using a peer-to-peer architecture, making it highly suitable for applications requiring quick data access.
  • Flexible Data Model
    Cassandra supports a flexible schema, allowing users to add new columns to a table at any time, making it adaptable for various use cases.
  • Geographical Distribution
    Data can be distributed across multiple data centers, ensuring low-latency access for geographically distributed users.
  • No Single Point of Failure
    Its decentralized nature ensures there is no single point of failure, which enhances resilience and fault-tolerance.

Possible disadvantages of Apache Cassandra

  • Complexity
    Managing and configuring Cassandra can be complex, requiring specialized knowledge and skills for optimal performance.
  • Eventual Consistency
    Cassandra follows an eventual consistency model, meaning that there might be a delay before all nodes have the latest data, which may not be suitable for all use cases.
  • Write-heavy Operations
    Although Cassandra handles writes efficiently, write-heavy workloads can lead to compaction issues and increased read latency.
  • Limited Query Capabilities
    Cassandra's query capabilities are relatively limited compared to traditional RDBMS, lacking support for complex joins and aggregations.
  • Maintenance Overhead
    Regular maintenance tasks such as node repair and compaction are necessary to ensure optimal performance, adding to the administrative overhead.
  • Tooling and Ecosystem
    While the ecosystem for Cassandra is growing, it is still not as extensive or mature as those for some other database technologies.

KNIME videos

+ Add

What Is KNIME?

More videos:

  • Review - KNIME Analytics: a Review
  • Review - Should you learn KNIME for machine learning: My thoughts after a month of use (2019)

Apache Cassandra videos

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Course Intro | DS101: Introduction to Apache Cassandra™

More videos:

  • Review - Introduction to Apache Cassandra™

Category Popularity

0-100% (relative to KNIME and Apache Cassandra)

KNIME

Apache Cassandra

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Databases
0 0%
Databases
100% 100
Business & Commerce
100 100%
Business & Commerce
0% 0
NoSQL Databases
0 0%
NoSQL Databases
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare KNIME and Apache Cassandra

KNIME Reviews

Top 10 Tableau Open Source Alternatives: A Comprehensive List
Knime Analytics Platform is an open-source Business Intelligence software that has been developed as an integration platform for creating analytical reports. It is a software that might be difficult for a novice to use. However, for Data Scientists and other Data professionals, particularly those who want to work with R, Python, or other Predictive Machine Learning tools,...
Source: hevodata.com
Top 10 Data Analysis Tools in 2022
KNIME KNIME is an open-source tool that allows you to build or manipulate software to fit your company goals. KNIME is a free data analysis tool. KNIME is a valuable tool that is freely accessible and can be modified due to its open architecture. However, there is a paucity of learning materials and a need for better visualization.
Source: www.spiceworks.com
15 data science tools to consider using in 2021
Some platforms are also available in free open source or community editions -- examples include Dataiku and H2O. Knime combines an open source analytics platform with a commercial Knime Server software package that supports team-based collaboration and workflow automation, deployment and management.
Source: searchbusinessanalytics.techtarget.com

Apache Cassandra Reviews

16 Top Big Data Analytics Tools You Should Know About
Application Areas: If you want to work with SQL-like data types on a No-SQL database, Cassandra is a good choice. It is a popular pick in the IoT, fraud detection applications, recommendation engines, product catalogs and playlists, and messaging applications, providing fast real-time insights.
Source: www.analytixlabs.co.in
9 Best MongoDB alternatives in 2019
The Apache Cassandra is an ideal choice for you if you want scalability and high availability without affecting its performance. This MongoDB alternative tool offers support for replicating across multiple datacenters.
Source: www.guru99.com

Social recommendations and mentions

Based on our record, Apache Cassandra seems to be a lot more popular than KNIME. While we know about 44 links to Apache Cassandra, we've tracked only 2 mentions of KNIME. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

KNIME mentions (2)

  • Replace SAP BI with what?
    I'd recommend to look into the free and open source KNIME tool (knime.com). It may not look easy to use right away, but if you stick with it for a little while and attend its learning guides, KNIME will grow on you. You can even have it scheduled using Microsoft Task Scheduler or CRON for free. For me, it has augmented the capabilities of Power BI, Looker Studio, Cognos, Excel, and other proprietary tools. Its... Source: almost 2 years ago
  • More "pythonic" way of writing my API query?
    That would cause a problem because ultimately this query will be scheduled to run multiple times a day on a KNIME server. Source: about 2 years ago

Apache Cassandra mentions (44)

  • Why You Shouldn’t Invest In Vector Databases?
    In fact, even in the absence of these commercial databases, users can effortlessly install PostgreSQL and leverage its built-in pgvector functionality for vector search. PostgreSQL stands as the benchmark in the realm of open-source databases, offering comprehensive support across various domains of database management. It excels in transaction processing (e.g., CockroachDB), online analytics (e.g., DuckDB),... - Source: dev.to / 22 days ago
  • Data integrity in Ably Pub/Sub
    All messages are persisted durably for two minutes, but Pub/Sub channels can be configured to persist messages for longer periods of time using the persisted messages feature. Persisted messages are additionally written to Cassandra. Multiple copies of the message are stored in a quorum of globally-distributed Cassandra nodes. - Source: dev.to / 6 months ago
  • Which Database is Perfect for You? A Comprehensive Guide to MySQL, PostgreSQL, NoSQL, and More
    Cassandra is a highly scalable, distributed NoSQL database designed to handle large amounts of data across many commodity servers without a single point of failure. - Source: dev.to / 11 months ago
  • Consistent Hashing: An Overview and Implementation in Golang
    Distributed storage Distributed storage systems like Cassandra, DynamoDB, and Voldemort also use consistent hashing. In these systems, data is partitioned across many servers. Consistent hashing is used to map data to the servers that store the data. When new servers are added or removed, consistent hashing minimizes the amount of data that needs to be remapped to different servers. - Source: dev.to / about 1 year ago
  • Understanding SQL vs. NoSQL Databases: A Beginner's Guide
    On the other hand, NoSQL databases are non-relational databases. They store data in flexible, JSON-like documents, key-value pairs, or wide-column stores. Examples include MongoDB, Couchbase, and Cassandra. - Source: dev.to / about 1 year ago
View more

What are some alternatives?

When comparing KNIME and Apache Cassandra, you can also consider the following products

datarobot - Become an AI-Driven Enterprise with Automated Machine Learning

Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.

RapidMiner - RapidMiner is a software platform for data science teams that unites data prep, machine learning, and predictive model deployment.

MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.

Montecarlito - MonteCarlito is a free Excel-add-in to do Monte-Carlo-simulations.

ArangoDB - A distributed open-source database with a flexible data model for documents, graphs, and key-values.

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