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  5. Azure Synapse vs GoodData

Azure Synapse vs GoodData

OverviewComparisonAlternatives

Overview

GoodData
GoodData
Stacks28
Followers44
Votes0
Azure Synapse
Azure Synapse
Stacks104
Followers230
Votes10

GoodData vs Azure Synapse: What are the differences?

What is GoodData? We help businesses monetize big data. Get a closer look at all your business data at the same time so you can gain actionable insight into sales, marketing, customer engagement and more.

What is Azure Synapse? Analytics service that brings together enterprise data warehousing and Big Data analytics. 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.

GoodData and Azure Synapse are primarily classified as "Business Intelligence" and "Big Data" tools respectively.

Some of the features offered by GoodData are:

  • Track all of your important business data in one place at the same time. Graphs and charts analyze changes in revenue, performance, website traffic, customer activity and more, and match these against your business goals.
  • Automatically segment your audiences, products, customer feedback and other important categories related to your business.
  • Set indicators to monitor the status of your business goals throughout the quarter. Goal indicators alert you when you’re on target, off pace and when something needs more attention to keep you on track, minimizing potential risks and surprises.

On the other hand, Azure Synapse provides the following key features:

  • Complete T-SQL based analytics – Generally Available
  • Deeply integrated Apache Spark
  • Hybrid data integration

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Detailed Comparison

GoodData
GoodData
Azure Synapse
Azure Synapse

Get a closer look at all your business data at the same time so you can gain actionable insight into sales, marketing, customer engagement and more.

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.

Track all of your important business data in one place at the same time. Graphs and charts analyze changes in revenue, performance, website traffic, customer activity and more, and match these against your business goals.;Automatically segment your audiences, products, customer feedback and other important categories related to your business.;Set indicators to monitor the status of your business goals throughout the quarter. Goal indicators alert you when you’re on target, off pace and when something needs more attention to keep you on track, minimizing potential risks and surprises.;Easily understand correlations between key business metrics: Does more effort and cost drive higher value deals? Which marketing lead sources have the highest ROI and conversion?;Measure activity at every stage of the sales funnel to identify which actions were taken, when they were taken and how many people took those actions. Compare these changes against previous weeks and set goals to evaluate the effectiveness of your campaign over a specific period of time.;Display multiple sets of related data for easy comparison. Using this information, you can identify differentiators and opportunities, and eliminate variables in your decision-making process.
Complete T-SQL based analytics – Generally Available; Deeply integrated Apache Spark; Hybrid data integration; Unified user experience
Statistics
Stacks
28
Stacks
104
Followers
44
Followers
230
Votes
0
Votes
10
Pros & Cons
No community feedback yet
Pros
  • 4
    ETL
  • 3
    Security
  • 2
    Serverless
  • 1
    Doesn't support cross database query
Cons
  • 1
    Concurrency
  • 1
    Dictionary Size Limitation - CCI

What are some alternatives to GoodData, Azure Synapse?

Metabase

Metabase

It is an easy way to generate charts and dashboards, ask simple ad hoc queries without using SQL, and see detailed information about rows in your Database. You can set it up in under 5 minutes, and then give yourself and others a place to ask simple questions and understand the data your application is generating.

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.

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.

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.

Presto

Presto

Distributed SQL Query Engine for Big Data

Amazon EMR

Amazon EMR

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

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.

Superset

Superset

Superset's main goal is to make it easy to slice, dice and visualize data. It empowers users to perform analytics at the speed of thought.

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.

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