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Treasure Data

27
43
+ 1
5
Xplenty

12
26
+ 1
2
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Treasure Data vs Xplenty: What are the differences?

What is Treasure Data? Flexible data analytics infrastructure as a service. 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.

What is Xplenty? Code-free data integration, data transformation and ETL in the cloud. Read and process data from cloud storage sources such as Amazon S3, Rackspace Cloud Files and IBM SoftLayer Object Storage. Once done processing, Xplenty allows you to connect with Amazon Redshift, SAP HANA and Google BigQuery. You can also store processed data back in your favorite relational database, cloud storage or key-value store.

Treasure Data and Xplenty can be categorized as "Big Data as a Service" tools.

Some of the features offered by Treasure Data are:

  • 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.

On the other hand, Xplenty provides the following key features:

  • Xplenty provides you with an visual, intuitive interface to design your ETL data flows
  • Xplenty lets you integrate data from a variety of data stores, such as Amazon RDS, MySQL, PostgreSQL, Microsoft SQL Server and MongoDB.
  • Read and process data from cloud storage sources such as Amazon S3, Rackspace Cloud Files and IBM SoftLayer Object Storage
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Pros of Treasure Data
Pros of Xplenty
  • 2
    Scaleability, less overhead
  • 2
    Makes it easy to ingest all data from different inputs
  • 1
    Responsive to our business requirements, great support
  • 2
    Simple, easy to integrate/process data without coding

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What is Treasure Data?

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.

What is Xplenty?

Read and process data from cloud storage sources such as Amazon S3, Rackspace Cloud Files and IBM SoftLayer Object Storage. Once done processing, Xplenty allows you to connect with Amazon Redshift, SAP HANA and Google BigQuery. You can also store processed data back in your favorite relational database, cloud storage or key-value store.

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What tools integrate with Xplenty?

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What are some alternatives to Treasure Data and Xplenty?
Fluentd
Fluentd collects events from various data sources and writes them to files, RDBMS, NoSQL, IaaS, SaaS, Hadoop and so on. Fluentd helps you unify your logging infrastructure.
Segment
Segment is a single hub for customer data. Collect your data in one place, then send it to more than 100 third-party tools, internal systems, or Amazon Redshift with the flip of a switch.
Splunk
It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.
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.
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.
See all alternatives