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
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.
What is Heroku Postgres?
What is Apache Spark?
Need advice about which tool to choose?Ask the StackShare community!
Sign up to add, upvote and see more prosMake informed product decisions
Sign up to get full access to all the companiesMake informed product decisions
Sign up to get full access to all the tool integrationsMake informed product decisions
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.
Rock solid transactional storage of user, purchase and course activity data. During development database dumps were easy to create and download locally for testing.
We use heroku PostgreSQL databases for testing alongside our sandboxed application(s) in heroku.
Extremely simple, practically a one-click setup.
Spark is good at parallel data processing management. We wrote a neat program to handle the TBs data we get everyday.
4 years of experience using Heroku Postgres for data storage and management.
Created several tables for users, brands, deals, campaigns, and tracking.