Data Lakehouse Software
Best Data Lakehouse Software include:
Databricks Lakehouse Platform, IBM watsonx.data, Delta Lake, Google BigLake and Microsoft Fabric.
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The Snowflake Cloud Data Platform is the eponymous data warehouse with, from the company in San Mateo, a cloud and SQL based DW that aims to allow users to unify, integrate, analyze, and share previously siloed data in secure, governed, and compliant ways. With it, users can securely…
Amazon Redshift is a hosted data warehouse solution, from Amazon Web Services.
Teradata Vantage is presented as a modern analytics cloud platform that unifies everything—data lakes, data warehouses, analytics, and new data sources and types. Supports hybrid multi-cloud environments and priced for flexibility, Vantage delivers unlimited intelligence to build…
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Databricks in San Francisco offers the Databricks Lakehouse Platform (formerly the Unified Analytics Platform), a data science platform and Apache Spark cluster manager. The Databricks Unified Data Service aims to provide a reliable and scalable platform for data pipelines, data…
Azure Synapse Analytics is described as the former Azure SQL Data Warehouse, evolved, and as a limitless analytics service that brings together enterprise data warehousing and Big Data analytics. It gives users the freedom to query data using either serverless or provisioned resources,…
Watsonx.data is presented as an open, hybrid and governed data store that makes it possible for enterprises to scale analytics and AI with a fit-for-purpose data store, built on an open lakehouse architecture, supported by querying, governance and open data formats to access and…
Amazon Athena is an interactive query service that makes it easy to analyze data directly in Amazon S3 using standard SQL. With a few clicks in the AWS Management Console, customers can point Athena at their data stored in S3 and begin using standard SQL to run ad-hoc queries and…
Qrvey headquartered in Tysons helps companies move their analytics beyond just visualizations and into the modern age with an all-in-one embedded analytics platform that was built on AWS to include the entire data pipeline. Qrvey includes tools for data collection, transformation,…
Cloudera Data Platform (CDP), launched September 2019, is designed to combine the best of Hortonworks and Cloudera technologies to deliver an enterprise data cloud. CDP includes the Cloudera Data Warehouse and machine learning services as well as a Data Hub service for building custom…
A data lakehouse deployed on-premise, in the cloud, or in a hybrid environment built on Apache Iceberg and Apache Spark, designed to address the evolving needs of the data landscape. It is presented as an anlternative to traditional Hadoop distributions: 1. Serverless Lakehouse: IOMETE…
Infor’s Data Lake tools deliver schema-on-read intelligence along with a flexible data consumption framework to enable new ways of making key decisions. With leveraged access tothe entire Infor ecosystem, users can start capturing and delivering big data to power next generation…
Built on years of investment in BigQuery, BigLake is a storage engine that allows organizations to unify data warehouses and lakes, and enable them to perform uniform fine-grained access control, and accelerate query performance across multi-cloud storage and open formats.
An automated no-code platform that provides data to value across different departments used for predictive analytics that help to make predictions about future outcomes using statistical algorithms, predictive modeling, and big data machine learning techniques. This helps organizations…
Delta Lake is an open source project that enables building a Lakehouse architecture on top of data lakes. Delta Lake provides ACID transactions, scalable metadata handling, and unifies streaming and batch data processing on top of existing data lakes, such as S3, ADLS, GCS, and HDFS.…
Microsoft Fabric: A Comprehensive Data Management SolutionMicrosoft Fabric presents a unified, robust platform designed to optimize data management, enhance AI model development, and empower users across an organization. It focuses on integrating data seamlessly, ensuring governance…
Learn More About Data Lakehouse Software
What are Data Lakehouses?
As businesses begin to use data from more and more sources simultaneously, it has become necessary to have repositories for large amounts of semi-structured data. These data sources are called data lakes. Data lakes allow for more flexibility in storage, at the expense of easy transaction support and schema governance. Though data warehouses allow for more control over the data, data lakes are an affordable way to store a lot of data from different sources.
A data lakehouse is an emerging technology that keeps the flexibility and openness of data lakes while expanding on their functionality to include some of the advanced features offered by data warehouses. Data lakehouses still hold data from many different sources, but they also allow for features more commonly associated with data warehouses, like concurrent data reading and writing, and additional support for data governance. These features enable real-time analytics tools that are becoming the norm in many industries. Data lakehouses are also highly scalable, allowing businesses to scale their compute resources up and down as needed.
The main benefit of a data lakehouse is a more affordable way to store disparate data compared to a data warehouse, without sacrificing the features like high-performance SQL.
Data Lakehouse Features & Capabilities:
The following features are common in Data Lakehouse solutions:
Schema support
Data reading and writing
End to end streaming
Transaction support
High performance SQL
Data Lakehouse Pricing Information:
Pricing for Data Lakehouses is highly dependent on the needs of the business. Most services allow users to turn compute resources on and off, so a diligent staff only has to pay for what they use. This also allows for simple scaling with a dynamic price point.