AI Powered Data Analysis for Smarter Decisions vs Azure Synapse

Overview

Azure Synapse

Stacks104

Followers230

Votes10

AI Powered Data Analysis for Smarter Decisions

Stacks0

Followers1

Votes1

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AI Powered Data Analysis for Smarter Decisions

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Detailed Comparison

Azure Synapse	AI Powered Data Analysis for Smarter Decisions
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.	Datums simplify data analysis with AI. Effortlessly integrate with major data warehouses, secure your data, and gain rapid, actionable insights. Join now!
Complete T-SQL based analytics – Generally Available; Deeply integrated Apache Spark; Hybrid data integration; Unified user experience	AI-powered data analytics, business intelligence platform
Statistics
Stacks 104	Stacks 0
Followers 230	Followers 1
Votes 10	Votes 1
Pros & Cons
Pros 4 ETL 3 Security 2 Serverless 1 Doesn't support cross database query Cons 1 Concurrency 1 Dictionary Size Limitation - CCI	No community feedback yet

What are some alternatives to Azure Synapse, AI Powered Data Analysis for Smarter Decisions?

Segment

Segment is a single hub for customer data. Collect your data in one place, then send it to more than 100 third-party tools, internal systems, or Amazon Redshift with the flip of a switch.

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

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

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

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

Presto

Distributed SQL Query Engine for Big Data

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 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.