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Apache HBase VS Altiscale Data Cloud

Compare Apache HBase VS Altiscale Data Cloud and see what are their differences

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Apache HBase logo Apache HBase

Apache HBase – Apache HBase™ Home

Altiscale Data Cloud logo Altiscale Data Cloud

Altiscale is a Hadoop-as-a-Service startup founded by ex-Yahoo CTO Raymie Stata designed to free users from the complexities of deploying, managing, and scaling a big data platform.
  • Apache HBase Landing page
    Landing page //
    2023-07-25
  • Altiscale Data Cloud Landing page
    Landing page //
    2021-12-17

Apache HBase features and specs

  • Scalability
    HBase is designed to scale horizontally, allowing it to handle large amounts of data by adding more nodes. This makes it suitable for applications requiring high write and read throughput.
  • Consistency
    It provides strong consistency for reads and writes, which ensures that any read will return the most recently written value. This is crucial for applications where data accuracy is essential.
  • Integration with Hadoop Ecosystem
    HBase integrates seamlessly with Hadoop and other components like Apache Hive and Apache Pig, making it a suitable choice for big data processing tasks.
  • Random Read/Write Access
    Unlike HDFS, HBase supports random, real-time read/write access to large datasets, making it ideal for applications that need frequent data updates.
  • Schema Flexibility
    HBase provides a flexible schema model that allows changes on demand without major disruptions, supporting dynamic and evolving data models.

Possible disadvantages of Apache HBase

  • Complexity
    Setting up and managing HBase can be complex and may require expert knowledge, especially for tuning and optimizing performance in large-scale deployments.
  • High Latency for Small Queries
    While HBase is designed for large-scale data, small queries can suffer from higher latency due to the overhead of its distributed nature.
  • Sparse Documentation
    Despite being widely used, HBase documentation and community support can sometimes be lacking, making issue resolution difficult for new users.
  • Dependency on Hadoop
    Since HBase depends heavily on the Hadoop ecosystem, issues or limitations with Hadoop components can affect HBase’s performance and functionality.
  • Limited Transaction Support
    HBase lacks full ACID transaction support, which can be a limitation for applications needing complex transactional processing.

Altiscale Data Cloud features and specs

No features have been listed yet.

Apache HBase videos

+ Add

Apache HBase 101: How HBase Can Help You Build Scalable, Distributed Java Applications

Altiscale Data Cloud videos

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Category Popularity

0-100% (relative to Apache HBase and Altiscale Data Cloud)

Apache HBase

Altiscale Data Cloud

Databases
100 100%
Databases
0% 0
Data Warehousing
0 0%
Data Warehousing
100% 100
NoSQL Databases
100 100%
NoSQL Databases
0% 0
Big Data
0 0%
Big Data
100% 100

User comments

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Social recommendations and mentions

Based on our record, Apache HBase seems to be more popular. It has been mentiond 8 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 HBase mentions (8)

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Altiscale Data Cloud mentions (0)

We have not tracked any mentions of Altiscale Data Cloud yet. Tracking of Altiscale Data Cloud recommendations started around Mar 2021.

What are some alternatives?

When comparing Apache HBase and Altiscale Data Cloud, you can also consider the following products

Apache Ambari - Ambari is aimed at making Hadoop management simpler by developing software for provisioning, managing, and monitoring Hadoop clusters.

Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.

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

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

Apache Pig - Pig is a high-level platform for creating MapReduce programs used with Hadoop.

Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?

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