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Apache Cassandra VS AWS IoT Analytics

Compare Apache Cassandra VS AWS IoT Analytics and see what are their differences

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Apache Cassandra logo Apache Cassandra

The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance.

AWS IoT Analytics logo AWS IoT Analytics

IoT Management
  • Apache Cassandra Landing page
    Landing page //
    2022-04-17
  • AWS IoT Analytics Landing page
    Landing page //
    2022-02-05

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.

AWS IoT Analytics features and specs

  • Scalable
    AWS IoT Analytics automatically scales to support large volumes of IoT data, accommodating billions of messages from millions of devices without the need for extensive infrastructure management.
  • Integration
    Seamlessly integrates with other AWS services like AWS Lambda, Amazon S3, and Amazon QuickSight for extended functionality and complete data processing and visualization workflows.
  • Time-series analysis
    Designed specifically to handle time-series data, providing tools and pre-built functions to analyze and visualize trends over time, which is crucial for monitoring IoT devices.
  • Data Enrichment
    Enables the enrichment of IoT data by integrating external data sources and using metadata, allowing for more contextual and meaningful data insights.
  • Machine Learning Support
    Supports integration with AWS's machine learning services, allowing users to build, train, and deploy models for predictive analysis directly on their IoT data.

Possible disadvantages of AWS IoT Analytics

  • Complexity
    The broad feature set and integration options can lead to a steep learning curve for users unfamiliar with AWS services and IoT analytics workflows.
  • Cost
    While offering extensive capabilities, the cost of using AWS IoT Analytics can become significant, especially as data volumes and processing needs increase.
  • Dependency on AWS Ecosystem
    Requires reliance on the AWS ecosystem, which can be a limitation for organizations using multi-cloud strategies or those wanting to maintain vendor neutrality.
  • Latency
    Although designed for handling IoT data, there can be latency issues in data processing and analysis, especially with high-frequency data ingestion.
  • Security Complexity
    Managing security and ensuring compliance can be complex due to the sensitive nature of IoT data and the need to configure various AWS security settings properly.

Apache Cassandra videos

Course Intro | DS101: Introduction to Apache Cassandra™

More videos:

  • Review - Introduction to Apache Cassandra™

AWS IoT Analytics videos

AWS IoT Analytics - How It Works

More videos:

  • Review - Learn Step by Step How iDevices Uses AWS IoT Analytics - AWS Online Tech Talks

Category Popularity

0-100% (relative to Apache Cassandra and AWS IoT Analytics)
Databases
100 100%
0% 0
Analytics
0 0%
100% 100
NoSQL Databases
100 100%
0% 0
Data Dashboard
0 0%
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 Apache Cassandra and AWS IoT Analytics

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.
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

AWS IoT Analytics Reviews

We have no reviews of AWS IoT Analytics yet.
Be the first one to post

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.

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
View more

AWS IoT Analytics mentions (0)

We have not tracked any mentions of AWS IoT Analytics yet. Tracking of AWS IoT Analytics recommendations started around Mar 2021.

What are some alternatives?

When comparing Apache Cassandra and AWS IoT Analytics, you can also consider the following products

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

ThingSpeak - Open source data platform for the Internet of Things. ThingSpeak Features

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

Countly - Product Analytics and Innovation. Build better customer journeys.

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

Azure IoT Hub - Manage billions of IoT devices with Azure IoT Hub, a cloud platform that lets you easily connect, monitor, provision, and configure IoT devices.