Azure Databricks
IBM Cloud Pak for Data
MyAnalytics
Arcadia Enterprise
MicroStrategy
MATLAB
Yandex.Metrica
Splunk Enterprise
Apache HBase
Apache Ambari
Apache Pig
Apache Cassandra
Apache Mahout
Apache Avro
Apache Oozie
Redis
Azure Databricks Apache HBaseBased on our record, Apache HBase should be more popular than Azure Databricks. It has been mentiond 6 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
In the big data space, Azure offers Azure Databricks. This is an Apache Spark big data analytics and machine learning service over a Distributed File System. The distributed cluster of nodes running analytics and AI operations in parallel allow for fast processing of large volumes of data and integration with popular machine learning libraries such as PyTorch unleash endless possibilities for custom ML. - Source: dev.to / almost 3 years ago
https://azure.microsoft.com/en-us/services/databricks. - Source: Hacker News / about 3 years ago
HBase and Cassandra: Both cater to non-structured Big Data. Cassandra is geared towards scenarios requiring high availability with eventual consistency, while HBase offers strong consistency and is better suited for read-heavy applications where data consistency is paramount. - Source: dev.to / 4 months ago
NoSQL databases are non-relational databases with flexible schema designed for high performance at a massive scale. Unlike traditional relational databases, which use tables and predefined schemas, NoSQL databases use a variety of data models. There are 4 main types of NoSQL databases - document, graph, key-value, and column-oriented databases. NoSQL databases generally are well-suited for unstructured data,... - Source: dev.to / 11 months ago
HBase, A scalable, distributed database that supports structured data storage for large tables. - Source: dev.to / over 1 year ago
Today, it is normal for enterprises to leverage diversified databases. In my market of expertise, China, in the Internet industry, MySQL together with data sharding middleware is the go to architecture, with GreenPlum, HBase, Elasticsearch, Clickhouse and other big data ecosystems being auxiliary computing engine for analytical data. At the same time, some legacy systems (such as SQLServer legacy from .NET... - Source: dev.to / about 2 years ago
For this type of systems PostgreSQL not best solution, and for a number of reasons like lack of replication out of the box. And we strictly must not have «Vendor lock», and therefore also did not take modern SQL databases like Amazon Aurora. And end of the ends the choice was made in favor Cassandra, for this article where we will talking about low-lever implementation of Repository Pattern it is not important, in... - Source: dev.to / over 2 years ago
IBM Cloud Pak for Data - Move to cloud faster with IBM Cloud Paks running on Red Hat OpenShift – fully integrated, open, containerized and secure solutions certified by IBM.
Apache Ambari - Ambari is aimed at making Hadoop management simpler by developing software for provisioning, managing, and monitoring Hadoop clusters.
MyAnalytics - MyAnalytics, now rebranded to Microsoft Viva Insights, is a customizable suite of tools that integrates with Office 365 to drive employee engagement and increase productivity.
Apache Pig - Pig is a high-level platform for creating MapReduce programs used with Hadoop.
Arcadia Enterprise - Arcadia Enterprise is the ultimate native BI for data lakes with real-time streaming visualizations, all without adding hardware or moving data.
Apache Cassandra - The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance.