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CLICK AI VS Apache Cassandra

Compare CLICK AI VS Apache Cassandra and see what are their differences

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CLICK AI logo CLICK AI

CLICK AI is an all-in-one artificial intelligence solution that provides many functions such as data collection, preprocessing, artificial intelligence modeling, prescriptive analysis, future prediction, and other functions with no coding required.

Apache Cassandra logo Apache Cassandra

The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance.
  • CLICK AI Landing page
    Landing page //
    2022-01-12

No need to hire AI developers or specialists to introduce new technology and diversify your business. This platform allows anyone to create deep learning-based AI models fast, with high accuracy, and without limitation by AI type/industry group.

With CLICK AI, you can use multiple data modeling features such as:

  • Automated Modeling
  • Classification
  • Image Classification
  • National Language Processing
  • Object Detection
  • Regression
  • Time Series Prediction
  • And much more!
  • Apache Cassandra Landing page
    Landing page //
    2022-04-17

CLICK AI features and specs

  • AI Powered
  • AI Analytics
  • Data Import/Export
  • No Coding Skills Required

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.

CLICK AI videos

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[INTRODUCTION TO CLICK AI] Experience CLICK AI, the best AI tool with just a few clicks!

Apache Cassandra videos

+ Add

Course Intro | DS101: Introduction to Apache Cassandra™

More videos:

  • Review - Introduction to Apache Cassandra™

Category Popularity

0-100% (relative to CLICK AI and Apache Cassandra)

CLICK AI

Apache Cassandra

AI
100 100%
AI
0% 0
Databases
0 0%
Databases
100% 100
Data Science And Machine Learning
100 100%
Data Science And Machine Learning
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 CLICK AI and Apache Cassandra

CLICK AI Reviews

We have no reviews of CLICK AI yet.
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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 more popular. It has been mentiond 44 times since March 2021. 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.

CLICK AI mentions (0)

We have not tracked any mentions of CLICK AI yet. Tracking of CLICK AI recommendations started around Mar 2021.

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 / 21 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
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What are some alternatives?

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

Lobe - Visual tool for building custom deep learning models

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

Neuro - Instant infrastructure for machine learning

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

mlblocks - A no-code Machine Learning solution. Made by teenagers.

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

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