Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.
Created by analysts, for analysts, Mode is a SQL-based analytics tool that connects directly to your database. Mode is designed to alleviate the bottlenecks in today's analytical workflow and drive collaboration around data projects. | 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. |
Write, save, and share SQL queries with other analysts in your company; Empower non-technical folks to update queries on their own; Run queries on a schedule, create lists of related reports, and explore a project's history as it changes over time;
Build reports using standard charting or create completely customer, interactive visuals with HTML, CSS, and Javascript;Database connectors for MySQL, Postgres, Redshift, Vertica, Hive, Heroku, Segment, BigQuery, Impala;
Mode also offers SQL School (sqlschool.modeanalytics.com), a free, interactive SQL tutorial and the Mode Playbook. | Complete T-SQL based analytics – Generally Available; Deeply integrated Apache Spark; Hybrid data integration; Unified user experience |
Statistics | |
Stacks 125 | Stacks 104 |
Followers 227 | Followers 230 |
Votes 17 | Votes 10 |
Pros & Cons | |
Pros
| Pros
Cons
|
Integrations | |
| No integrations available | |
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.
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.
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.
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 is a cloud based service that makes big data easy for analysts and data engineers.
Distributed SQL Query Engine for Big Data
It is used in a variety of applications, including log analysis, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics.
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'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 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.
