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1010Data VS Apache Cassandra

Compare 1010Data VS Apache Cassandra and see what are their differences

Draxlr
Turn SQL Data into Decisions. Build professional dashboards and data visualizations without technical expertise. Easily embed analytics anywhere, receive automated alerts, and discover AI-powered insights all through a straightforward interface. featured
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1010Data logo 1010Data

1010data provides cloud-based big data analytics for retail, manufacturing, telecom and financial services enterprises.

Apache Cassandra logo Apache Cassandra

The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance.
  • 1010Data Landing page
    Landing page //
    2023-10-04
  • Apache Cassandra Landing page
    Landing page //
    2022-04-17

1010Data features and specs

  • Scalability
    1010Data is designed to handle massive datasets, making it suitable for large enterprises that require powerful data processing capabilities.
  • Ease of Use
    The platform offers a user-friendly interface and intuitive data analysis tools, which can ease the learning curve for new users.
  • Integrated Platform
    1010Data provides a unified platform that combines data storage, processing, and analytics, allowing for seamless data management and analysis.
  • Real-Time Analytics
    The platform supports real-time data analysis, enabling businesses to make timely decisions based on the latest data insights.
  • Strong Security Measures
    1010Data implements robust security protocols, ensuring that sensitive data is protected against unauthorized access.
  • Industry-Specific Solutions
    The platform offers tailored solutions for various industries such as retail, finance, and healthcare, helping users meet sector-specific requirements.

Possible disadvantages of 1010Data

  • Cost
    The platform can be expensive for small to medium-sized businesses, potentially putting it out of reach for organizations with limited budgets.
  • Complexity for Advanced Users
    While 1010Data is user-friendly, more advanced users may find the platform's limitations restricting for highly complex or custom analyses.
  • Integration Challenges
    Integrating 1010Data with existing systems and workflows can be complex and might require additional resources and time.
  • Steep Learning Curve for Advanced Features
    Despite the easy-to-use interface, mastering the platform's advanced features may require significant training and expertise.
  • Performance Issues with Extremely Large Datasets
    Although designed for scalability, performance can degrade when working with extremely large datasets or very complex queries.
  • Limited Offline Capabilities
    1010Data is primarily cloud-based, which can be a limitation for users needing robust offline functionality for data analysis.

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.

1010Data videos

+ Add

Introduction to 1010data

More videos:

  • Review - 1010data Employee Reviews - Q3 2018
  • Review - 1010data Company Overview

Apache Cassandra videos

+ Add

Course Intro | DS101: Introduction to Apache Cassandra™

More videos:

  • Review - Introduction to Apache Cassandra™

Category Popularity

0-100% (relative to 1010Data and Apache Cassandra)

1010Data

Apache Cassandra

Data Dashboard
100 100%
Data Dashboard
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 1010Data and Apache Cassandra

1010Data Reviews

We have no reviews of 1010Data 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 a lot more popular than 1010Data. While we know about 44 links to Apache Cassandra, we've tracked only 1 mention of 1010Data. 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.

1010Data mentions (1)

  • Where to get this kind of graph?
    Everything costs money. If you buy a subscription to https://www.vandaresearch.com/ you'll get this. If you buy a subscription to 1010data.com you'll get good info. If you're getting your info from WSB you're betting on epsilon, not alpha. Source: almost 3 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
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What are some alternatives?

When comparing 1010Data and Apache Cassandra, you can also consider the following products

Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.

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

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

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

Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.

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

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