Apache Spark

Apache Spark

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Score 8.7 out of 100
Apache Spark

Overview

Recent Reviews

Apache Spark in Telco

10 out of 10
July 22, 2021
Apache Spark is being widely used within the company. In Advanced Analytics department data engineers and data scientists work closely in …
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A powerhouse processing engine.

9 out of 10
September 19, 2020
We use Apache Spark for cluster computing in large-scale data processing, ETL functions, machine learning, as well as for analytics. Its …
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Apache Spark Review

7 out of 10
March 16, 2019
We used Apache Spark within our department as a Solution Architecture team. It helped make big data processing more efficient since the …
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Alternatives Pricing

What is Databricks Lakehouse Platform?

Databricks in San Francisco offers the Databricks Lakehouse Platform (formerly the Unified Analytics Platform), a data science platform and Apache Spark cluster manager. The Databricks Unified Data Service aims to provide a reliable and scalable platform for data pipelines, data lakes, and data…

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Product Details

What is Apache Spark?

Apache Spark Technical Details

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Reviews and Ratings

 (149)

Ratings

Reviews

(1-4 of 4)
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Score 9 out of 10
Vetted Review
Verified User
Review Source
Never had to contact them, however, they offer 24/7 support and there are a large number of forums about Spark, well-integrated with python and supports SQL syntaxis.
Score 8 out of 10
Vetted Review
Verified User
Review Source
1. It integrates very well with scala or python.
2. It's very easy to understand SQL interoperability.
3. Apache is way faster than the other competitive technologies.
4. The support from the Apache community is very huge for Spark.
5. Execution times are faster as compared to others.
6. There are a large number of forums available for Apache Spark.
7. The code availability for Apache Spark is simpler and easy to gain access to.
8. Many organizations use Apache Spark, so many solutions are available for existing applications.
Score 9 out of 10
Vetted Review
Verified User
Review Source
As every open source tool, you have to use forums, consulting companies and engineering power to support and maintain. There is plenty of documentation available, so you will be in good hands. You can also find consulting companies small-mid size which can support your environment at a decent cost. Another alternative is going to Data Bricks, if support is a key criteria for your decision.