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  1. Stackups
  2. Application & Data
  3. Databases
  4. Big Data As A Service
  5. Amazon EMR vs Census

Amazon EMR vs Census

OverviewComparisonAlternatives

Overview

Amazon EMR
Amazon EMR
Stacks542
Followers682
Votes54
Census
Census
Stacks22
Followers27
Votes0

Amazon EMR vs Census: What are the differences?

What is Amazon EMR? Distribute your data and processing across a Amazon EC2 instances using Hadoop. It is used in a variety of applications, including log analysis, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics.

What is Census? Sync your warehouse data to any app. It syncs your data warehouse with CRM & go-to-market tools. Get your customer success, sales & marketing teams on the same page by sharing the same customer data.

Amazon EMR and Census can be categorized as "Big Data as a Service" tools.

Some of the features offered by Amazon EMR are:

  • Elastic- Amazon EMR enables you to quickly and easily provision as much capacity as you need and add or remove capacity at any time. Deploy multiple clusters or resize a running cluster
  • Low Cost- Amazon EMR is designed to reduce the cost of processing large amounts of data. Some of the features that make it low cost include low hourly pricing, Amazon EC2 Spot integration, Amazon EC2 Reserved Instance integration, elasticity, and Amazon S3 integration.
  • Flexible Data Stores- With Amazon EMR, you can leverage multiple data stores, including Amazon S3, the Hadoop Distributed File System (HDFS), and Amazon DynamoDB.

On the other hand, Census provides the following key features:

  • Turn your warehouse into a Customer Data Platform
  • Sync with customer facing tools
  • No more data outages

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Detailed Comparison

Amazon EMR
Amazon EMR
Census
Census

It is used in a variety of applications, including log analysis, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics.

It syncs your data warehouse with CRM & go-to-market tools. Get your customer success, sales & marketing teams on the same page by sharing the same customer data.

Elastic- Amazon EMR enables you to quickly and easily provision as much capacity as you need and add or remove capacity at any time. Deploy multiple clusters or resize a running cluster;Low Cost- Amazon EMR is designed to reduce the cost of processing large amounts of data. Some of the features that make it low cost include low hourly pricing, Amazon EC2 Spot integration, Amazon EC2 Reserved Instance integration, elasticity, and Amazon S3 integration.;Flexible Data Stores- With Amazon EMR, you can leverage multiple data stores, including Amazon S3, the Hadoop Distributed File System (HDFS), and Amazon DynamoDB.;Hadoop Tools- EMR supports powerful and proven Hadoop tools such as Hive, Pig, and HBase.
Turn your warehouse into a Customer Data Platform; Sync with customer facing tools; No more data outages
Statistics
Stacks
542
Stacks
22
Followers
682
Followers
27
Votes
54
Votes
0
Pros & Cons
Pros
  • 15
    On demand processing power
  • 12
    Don't need to maintain Hadoop Cluster yourself
  • 7
    Hadoop Tools
  • 6
    Elastic
  • 4
    Backed by Amazon
No community feedback yet
Integrations
No integrations available
Amazon Redshift
Amazon Redshift
Google BigQuery
Google BigQuery
Outreach.io
Outreach.io
Google Sheets
Google Sheets
Pipedrive
Pipedrive
Snowflake
Snowflake
Customer.io
Customer.io
Iterable
Iterable
Marketo
Marketo
Braze
Braze

What are some alternatives to Amazon EMR, Census?

Google BigQuery

Google BigQuery

Run super-fast, SQL-like queries against terabytes of data in seconds, using the processing power of Google's infrastructure. Load data with ease. Bulk load your data using Google Cloud Storage or stream it in. Easy access. Access BigQuery by using a browser tool, a command-line tool, or by making calls to the BigQuery REST API with client libraries such as Java, PHP or Python.

Amazon Redshift

Amazon Redshift

It is optimized for data sets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.

Qubole

Qubole

Qubole is a cloud based service that makes big data easy for analysts and data engineers.

Altiscale

Altiscale

we run Apache Hadoop for you. We not only deploy Hadoop, we monitor, manage, fix, and update it for you. Then we take it a step further: We monitor your jobs, notify you when something’s wrong with them, and can help with tuning.

Snowflake

Snowflake

Snowflake eliminates the administration and management demands of traditional data warehouses and big data platforms. Snowflake is a true data warehouse as a service running on Amazon Web Services (AWS)—no infrastructure to manage and no knobs to turn.

Stitch

Stitch

Stitch is a simple, powerful ETL service built for software developers. Stitch evolved out of RJMetrics, a widely used business intelligence platform. When RJMetrics was acquired by Magento in 2016, Stitch was launched as its own company.

Azure Synapse

Azure Synapse

It is an analytics service that brings together enterprise data warehousing and Big Data analytics. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources—at scale. It brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs.

Dremio

Dremio

Dremio—the data lake engine, operationalizes your data lake storage and speeds your analytics processes with a high-performance and high-efficiency query engine while also democratizing data access for data scientists and analysts.

Cloudera Enterprise

Cloudera Enterprise

Cloudera Enterprise includes CDH, the world’s most popular open source Hadoop-based platform, as well as advanced system management and data management tools plus dedicated support and community advocacy from our world-class team of Hadoop developers and experts.

Airbyte

Airbyte

It is an open-source data integration platform that syncs data from applications, APIs & databases to data warehouses lakes & DBs.

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