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  1. Stackups
  2. Application & Data
  3. Relational Databases
  4. Postgresql As A Service
  5. Druid vs Heroku Postgres

Druid vs Heroku Postgres

OverviewDecisionsComparisonAlternatives

Overview

Heroku Postgres
Heroku Postgres
Stacks607
Followers314
Votes38
Druid
Druid
Stacks377
Followers867
Votes32

Druid vs Heroku Postgres: What are the differences?

What is Druid? Fast column-oriented distributed data store. Druid is a distributed, column-oriented, real-time analytics data store that is commonly used to power exploratory dashboards in multi-tenant environments. Druid excels as a data warehousing solution for fast aggregate queries on petabyte sized data sets. Druid supports a variety of flexible filters, exact calculations, approximate algorithms, and other useful calculations.

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.

Druid can be classified as a tool in the "Big Data Tools" category, while Heroku Postgres is grouped under "PostgreSQL as a Service".

"Real Time Aggregations" is the primary reason why developers consider Druid over the competitors, whereas "Easy to setup" was stated as the key factor in picking Heroku Postgres.

Druid is an open source tool with 8.22K GitHub stars and 2.05K GitHub forks. Here's a link to Druid's open source repository on GitHub.

According to the StackShare community, Heroku Postgres has a broader approval, being mentioned in 74 company stacks & 38 developers stacks; compared to Druid, which is listed in 24 company stacks and 12 developer stacks.

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Advice on Heroku Postgres, Druid

Jorge
Jorge

Jan 15, 2020

Needs advice

Considering moving part of our PostgreSQL database infrastructure to the cloud, however, not quite sure between AWS, Heroku, Azure and Google cloud. Things to consider: The main reason is for backing up and centralize all our data in the cloud. With that in mind the main elements are: -Pricing for storage. -Small team. -No need for high throughput. -Support for docker swarm and Kubernetes.

51.8k views51.8k
Comments

Detailed Comparison

Heroku Postgres
Heroku Postgres
Druid
Druid

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

Druid is a distributed, column-oriented, real-time analytics data store that is commonly used to power exploratory dashboards in multi-tenant environments. Druid excels as a data warehousing solution for fast aggregate queries on petabyte sized data sets. Druid supports a variety of flexible filters, exact calculations, approximate algorithms, and other useful calculations.

High Availability;Rollback;Dataclips;Automated Health Checks
-
Statistics
Stacks
607
Stacks
377
Followers
314
Followers
867
Votes
38
Votes
32
Pros & Cons
Pros
  • 29
    Easy to setup
  • 3
    Extremely reliable
  • 3
    Dataclips for sharing queries
  • 3
    Follower databases
Cons
  • 2
    Super expensive
Pros
  • 15
    Real Time Aggregations
  • 6
    Batch and Real-Time Ingestion
  • 5
    OLAP
  • 3
    OLAP + OLTP
  • 2
    Combining stream and historical analytics
Cons
  • 3
    Limited sql support
  • 2
    Joins are not supported well
  • 1
    Complexity
Integrations
PostgreSQL
PostgreSQL
Heroku
Heroku
Zookeeper
Zookeeper

What are some alternatives to Heroku Postgres, Druid?

Apache Spark

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.

Presto

Presto

Distributed SQL Query Engine for Big Data

Amazon Athena

Amazon Athena

Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.

Amazon RDS for PostgreSQL

Amazon RDS for PostgreSQL

Amazon RDS manages complex and time-consuming administrative tasks such as PostgreSQL software installation and upgrades, storage management, replication for high availability and back-ups for disaster recovery. With just a few clicks in the AWS Management Console, you can deploy a PostgreSQL database with automatically configured database parameters for optimal performance. Amazon RDS for PostgreSQL database instances can be provisioned with either standard storage or Provisioned IOPS storage. Once provisioned, you can scale from 10GB to 3TB of storage and from 1,000 IOPS to 30,000 IOPS.

Apache Flink

Apache Flink

Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.

lakeFS

lakeFS

It is an open-source data version control system for data lakes. It provides a “Git for data” platform enabling you to implement best practices from software engineering on your data lake, including branching and merging, CI/CD, and production-like dev/test environments.

Apache Kylin

Apache Kylin

Apache Kylin™ is an open source Distributed Analytics Engine designed to provide SQL interface and multi-dimensional analysis (OLAP) on Hadoop/Spark supporting extremely large datasets, originally contributed from eBay Inc.

Splunk

Splunk

It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.

Apache Impala

Apache Impala

Impala is a modern, open source, MPP SQL query engine for Apache Hadoop. Impala is shipped by Cloudera, MapR, and Amazon. With Impala, you can query data, whether stored in HDFS or Apache HBase – including SELECT, JOIN, and aggregate functions – in real time.

Vertica

Vertica

It provides a best-in-class, unified analytics platform that will forever be independent from underlying infrastructure.

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