Azure Data Lake Store
Google BigQuery
Qubole
Amazon EMR
Snowflake
Azure HDInsight
Google Cloud Dataflow
Databricks
Apache HBase
Apache Ambari
Apache Pig
Apache Mahout
Apache Cassandra
Apache Avro
Apache Oozie
Redis
Azure Data Lake Store Apache HBaseNo Azure Data Lake Store videos yet. You could help us improve this page by suggesting one.
Based on our record, Apache HBase should be more popular than Azure Data Lake Store. 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.
If you're deploying applications to the cloud, you'll need persistent data storage. Azure Blob Storage allows scalable storage for objects and files and provides an SDK to easily access them. Blob storage is a great trigger for Azure Functions, where uploading a file can automatically run your custom logic in the cloud (for example, if you wanted to run OCR on a file as soon as it's uploaded to a storage... - Source: dev.to / almost 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 / 3 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 / 10 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 / about 2 years ago
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
Apache Ambari - Ambari is aimed at making Hadoop management simpler by developing software for provisioning, managing, and monitoring Hadoop clusters.
Qubole - Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.
Apache Pig - Pig is a high-level platform for creating MapReduce programs used with Hadoop.
Amazon EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.
Apache Mahout - Distributed Linear Algebra
