Big Data Technologies and Services Providers

Big Data Orgs

Comparative analysis of all Big Data technologies and services providers are available. Please connect with this for a copy.

First Group of Big Data Product

The product set up starts with defining role or key that is used to access cloud and granting permission to use cloud for the product. The set up is completed through installing and configuring control and data plane. The control resides at the product provider while data plane belongs to user. There is tunnel between control and data planes. There are various license types which basically allow users to get access at software or platform or infrastructure layer or combinations of these while getting on these Big Data Product. These layers are further combined in compute engines and storage. The license type is just providing access to compute layers or engines or storage. There are more customized features and functionalities. These features and functionalities are accessible through ODBC/JDBC/SDK/API/UI. Auto scale happens in the cloud on the behalf of the product when loads increase or decrease. 

Big Data Orgs first Category
Big Data Orgs second Category

Second Group of Big Data Product

For this category of product, the product set up starts with creating and configuring environment & cluster meta, and provisioning technical stack. Three parameters value are set for Big Data. These parameters are number of master nodes, number of worker nodes, and number of scheduler nodes. There is need to select machine type for these nodes. Once cluster or technical stack is ready, the cluster can be started. There are various out of box tools or third party tools used to interact with clusters and hence Big Data engines. Such a set up has out of box features and functionalities. These features and functionalities are accessible through ODBC/JDBC/SDK/API/UI. Auto scale happens in the cloud on the behalf of the product when loads increase or decrease. 

Data Lake

A data lake is a centralized repository that allows you to store all your structured and unstructured data at any scale. You can store your data as-is, without having to first structure the data, and run different types of analytics—from dashboards and visualizations to big data processing, real-time analytics, and machine learning to guide better decisions. There are cloud provider Data Lake as well as Open Source Data Lake

  • AWS Data Lake
  • Azure Data Lake
  • Google Data Lake
  • Cloudera Data Lake
  • Databricks Data Lake
  • Snowflake Data Lake
  • Apache Iceberg
  • Delta Lake
Data Lake

Some of Big Data Organization from First Group 

  • Databricks - Unify all your data, analytics and AI on one platform
  • Snowflake - Cloud-based data warehousing platform with separation of compute and storage
  • Vertica - Performance analytical database for real-time analytics
  • Confluent - Streaming platform for managing and processing high volumes of real-time data
  • Starburst - Open-source distributed SQL query engine to query data across disparate sources
  • Dremio - Its ability to accelerate data access and analytics on data lakes
  • Qubole - Qubole is an open, simple, and secure data lake platform
  • Control-M - Transform business with application and data workflow orchestration
  • Posit - Deploy all your work, including Shiny, Streamlit, and Dash applications, Models
  • Tlmi - Specialists in Machine Learning, AI, Big Data and BI
  • Snowplow - Event data collection and analytics platform with flexibility and extensibility
  • Cloudera - Enterprise-grade platform, which combines open-source technologies
  • Vantage - Provides advanced Big Data capabilities
  • Druid - High performance, real-time analytics database 
  • Aerospike - High-performance, low-latency NoSQL database
  • Beam - Unified programming model for batch and streaming data processing

Some of Big Data Organization from Second Group 

  • AWS EMR - Easily run and scale Apache Spark, Hive, Presto, and other big data workloads
  • AWS Managed Airflow - Highly available managed workflow orchestration for Apache Airflow
  • IBM Big Data - Leverage effective big data technologies
  • Azure Big Data - How big data analytics works and why it matters
  • Oracle Big Data - Help data professionals manage, catalog, and process raw data
  • GCP Big Query - BigQuery is a serverless and cost-effective enterprise data warehouse

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