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Heroku Postgres
Heroku Postgres

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Heroku Postgres vs Apache Spark: What are the differences?

What is Heroku Postgres? Heroku's Database-as-a-Service. Based on the most powerful open-source database, PostgreSQL. Heroku Postgres provides a SQL database-as-a-service that lets you focus on building your application instead of messing around with database management.

What is Apache Spark? Fast and general engine for large-scale data processing. Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.

Heroku Postgres and Apache Spark are primarily classified as "PostgreSQL as a Service" and "Big Data" tools respectively.

Some of the features offered by Heroku Postgres are:

  • High Availability
  • Rollback
  • Dataclips

On the other hand, Apache Spark provides the following key features:

  • Run programs up to 100x faster than Hadoop MapReduce in memory, or 10x faster on disk
  • Write applications quickly in Java, Scala or Python
  • Combine SQL, streaming, and complex analytics

"Easy to setup" is the top reason why over 27 developers like Heroku Postgres, while over 45 developers mention "Open-source" as the leading cause for choosing Apache Spark.

Apache Spark is an open source tool with 22.3K GitHub stars and 19.3K GitHub forks. Here's a link to Apache Spark's open source repository on GitHub.

According to the StackShare community, Apache Spark has a broader approval, being mentioned in 263 company stacks & 111 developers stacks; compared to Heroku Postgres, which is listed in 74 company stacks and 38 developer stacks.

- No public GitHub repository available -

What is Heroku Postgres?

Heroku Postgres provides a SQL database-as-a-service that lets you focus on building your application instead of messing around with database management.

What is Apache Spark?

Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
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What are some alternatives to Heroku Postgres and Apache Spark?
MongoDB
MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
ClearDB
ClearDB uses a combination of advanced replication techniques, advanced cluster technology, and layered web services to provide you with a MySQL database that is "smarter" than usual.
Heroku
Heroku is a cloud application platform – a new way of building and deploying web apps. Heroku lets app developers spend 100% of their time on their application code, not managing servers, deployment, ongoing operations, or scaling.
Google Cloud SQL
MySQL databases deployed in the cloud without a fuss. Google Cloud Platform provides you with powerful databases that run fast, don’t run out of space and give your application the redundant, reliable storage it needs.
Heroku Redis
Heroku Redis is an in-memory key-value data store, run by Heroku, that is provisioned and managed as an add-on. Heroku Redis is accessible from any language with a Redis driver, including all languages and frameworks supported by Heroku.
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Decisions about Heroku Postgres and Apache Spark
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How developers use Heroku Postgres and Apache Spark
Avatar of PSESD
PSESD uses Heroku PostgresHeroku Postgres

Stores the admin database for the SRX apps - includes an audit log, error tracking, and SRX admin message log.

Will also store PRS rules when refactor is complete.

Avatar of Tim Lucas
Tim Lucas uses Heroku PostgresHeroku Postgres

Rock solid transactional storage of user, purchase and course activity data. During development database dumps were easy to create and download locally for testing.

Avatar of datapile
datapile uses Heroku PostgresHeroku Postgres

We use heroku PostgreSQL databases for testing alongside our sandboxed application(s) in heroku.

Extremely simple, practically a one-click setup.

Avatar of Wei Chen
Wei Chen uses Apache SparkApache Spark

Spark is good at parallel data processing management. We wrote a neat program to handle the TBs data we get everyday.

Avatar of Hunt Norment
Hunt Norment uses Heroku PostgresHeroku Postgres

4 years of experience using Heroku Postgres for data storage and management.

Avatar of Kyle Fretwell
Kyle Fretwell uses Heroku PostgresHeroku Postgres

Created several tables for users, brands, deals, campaigns, and tracking.

Avatar of Ralic Lo
Ralic Lo uses Apache SparkApache Spark

Used Spark Dataframe API on Spark-R for big data analysis.

Avatar of BrainFinance
BrainFinance uses Apache SparkApache Spark

As a part of big data machine learning stack (SMACK).

Avatar of Kalibrr
Kalibrr uses Apache SparkApache Spark

We use Apache Spark in computing our recommendations.

Avatar of Dotmetrics
Dotmetrics uses Apache SparkApache Spark

Big data analytics and nightly transformation jobs.

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