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  1. Stackups
  2. Application & Data
  3. Databases
  4. Big Data Tools
  5. Amazon AppFlow vs Mara

Amazon AppFlow vs Mara

OverviewComparisonAlternatives

Overview

Mara
Mara
Stacks5
Followers21
Votes3
Amazon AppFlow
Amazon AppFlow
Stacks9
Followers42
Votes0

Mara vs Amazon AppFlow: What are the differences?

Mara: A lightweight ETL framework. A lightweight ETL framework with a focus on transparency and complexity reduction; Amazon AppFlow: *Securely integrate apps and automate data flows at any scale, without code *. It is a fully managed integration service that enables you to securely transfer data between Software-as-a-Service (SaaS) applications like Salesforce, Marketo, Slack, and ServiceNow, and AWS services like Amazon S3 and Amazon Redshift, in just a few clicks. With AppFlow, you can run data flows at nearly any scale at the frequency you choose - on a schedule, in response to a business event, or on demand. You can configure data transformation capabilities like filtering and validation to generate rich, ready-to-use data as part of the flow itself, without additional steps. AppFlow automatically encrypts data in motion, and allows users to restrict data from flowing over the public Internet for SaaS applications that are integrated with AWS PrivateLink, reducing exposure to security threats.

Mara and Amazon AppFlow can be primarily classified as "Big Data" tools.

Some of the features offered by Mara are:

  • Data integration pipelines as code: pipelines, tasks and commands are created using declarative Python code.
  • PostgreSQL as a data processing engine.
  • Extensive web ui. The web browser as the main tool for inspecting, running and debugging pipelines.

On the other hand, Amazon AppFlow provides the following key features:

  • Point and click user interface
  • Native SaaS integrations
  • Enterprise grade data transformations

Mara is an open source tool with 1.45K GitHub stars and 69 GitHub forks. Here's a link to Mara's open source repository on GitHub.

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Detailed Comparison

Mara
Mara
Amazon AppFlow
Amazon AppFlow

A lightweight ETL framework with a focus on transparency and complexity reduction.

It is a fully managed integration service that enables you to securely transfer data between Software-as-a-Service (SaaS) applications like Salesforce, Marketo, Slack, and ServiceNow, and AWS services like Amazon S3 and Amazon Redshift, in just a few clicks. With AppFlow, you can run data flows at nearly any scale at the frequency you choose - on a schedule, in response to a business event, or on demand. You can configure data transformation capabilities like filtering and validation to generate rich, ready-to-use data as part of the flow itself, without additional steps. AppFlow automatically encrypts data in motion, and allows users to restrict data from flowing over the public Internet for SaaS applications that are integrated with AWS PrivateLink, reducing exposure to security threats.

Data integration pipelines as code: pipelines, tasks and commands are created using declarative Python code.; PostgreSQL as a data processing engine.; Extensive web ui. The web browser as the main tool for inspecting, running and debugging pipelines.; GNU make semantics. Nodes depend on the completion of upstream nodes. No data dependencies or data flows.; No in-app data processing: command line tools as the main tool for interacting with databases and data.; Single machine pipeline execution based on Python's multiprocessing. No need for distributed task queues. Easy debugging and and output logging.; Cost based priority queues: nodes with higher cost (based on recorded run times) are run first.
Point and click user interface; Native SaaS integrations; Enterprise grade data transformations; High scale data transfer; Data privacy defaults through PrivateLink; Custom encryption keys; IAM policy enforcement; Flexible data flow triggers; Easy to use field mapping; Built in reliability
Statistics
Stacks
5
Stacks
9
Followers
21
Followers
42
Votes
3
Votes
0
Pros & Cons
Pros
  • 1
    Great developing experience
  • 1
    ETL Tool
  • 1
    UI focused on ETL development
No community feedback yet
Integrations
No integrations available
Google Analytics
Google Analytics
Slack
Slack
Dynatrace
Dynatrace
Datadog
Datadog
Zendesk
Zendesk
Marketo
Marketo
Snowflake
Snowflake
Amplitude
Amplitude
Veeva
Veeva

What are some alternatives to Mara, Amazon AppFlow?

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.

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.

Druid

Druid

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.

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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