Azure HDInsight vs Treasure Data
Overview
🔥 Trending in Databases on StackShare
Detailed Comparison
Treasure Data's Big Data as-a-Service cloud platform enables data-driven businesses to focus their precious development resources on their applications, not on mundane, time-consuming integration and operational tasks. The Treasure Data Cloud Data Warehouse service offers an affordable, quick-to-implement and easy-to-use big data option that does not require specialized IT resources, making big data analytics available to the mass market. | It is a cloud-based service from Microsoft for big data analytics that helps organizations process large amounts of streaming or historical data. |
Instant Integration- Using td-agent, you can start importing your data from existing log files, web and packaged applications right away.;Streaming or Batch?- You choose! Our data collection tool, td-agent, enables you to stream or batch your data to the cloud in JSON format.;Secure Upload- The connection between td-agent and the cloud is SSL-encrypted, ensuring secure transfer of your data.;Availability- Our best-in-class, multi-tenant architecture uses Amazon S3 to ensure 24x7 availability and automatic replication.;Columnar Database- Our columnar database not only delivers blinding performance, it also compresses data to 5 to 10 percent of its original size.;Schema Free- Unlike traditional databases – even cloud databases – Treasure Data allows you to change your data schema anytime.;SQL-like Query Language- Query your data using our SQL-like language.;BI Tools Connectivity- Treasure Data allows you to use your existing BI/visualization tools (e.g. JasperSoft, Pentaho, Talend, Indicee, Metric Insights) using our JDBC driver.;Enterprise-level Service and Support;No Lock-in- We provide a one-line command to let you export your data anywhere you choose, whenever you choose. | Fully managed;
Full-spectrum;
Open-source analytics service in the cloud for enterprises |
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Stacks 28 | Stacks 29 |
Followers 44 | Followers 138 |
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What are some alternatives to Treasure Data, Azure HDInsight?
Google BigQuery
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.
Apache Spark
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.
Amazon Redshift
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
Qubole is a cloud based service that makes big data easy for analysts and data engineers.
Presto
Distributed SQL Query Engine for Big Data
Amazon EMR
It is used in a variety of applications, including log analysis, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics.
Amazon Athena
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.
Apache Flink
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.
lakeFS
It is an open-source data version control system for data lakes. It provides a “Git for data” platform enabling you to implement best practices from software engineering on your data lake, including branching and merging, CI/CD, and production-like dev/test environments.
Druid
Druid is a distributed, column-oriented, real-time analytics data store that is commonly used to power exploratory dashboards in multi-tenant environments. Druid excels as a data warehousing solution for fast aggregate queries on petabyte sized data sets. Druid supports a variety of flexible filters, exact calculations, approximate algorithms, and other useful calculations.
