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.
Treasure Data is a tool in the Big Data as a Service category of a tech stack.

Who uses Treasure Data?

7 companies reportedly use Treasure Data in their tech stacks, including Wantedly, OTOBANK Inc., and FiveStars.

7 developers on StackShare have stated that they use Treasure Data.

Treasure Data Integrations

Amazon EC2, Heroku, Engine Yard Cloud, OpenShift, and cloudControl are some of the popular tools that integrate with Treasure Data. Here's a list of all 9 tools that integrate with Treasure Data.

Why developers like Treasure Data?

Here’s a list of reasons why companies and developers use Treasure Data

Treasure Data's Features

  • 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.

Treasure Data Alternatives & Comparisons

What are some alternatives to Treasure Data?
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.
Amazon Redshift
Redshift makes it simple and cost-effective to efficiently analyze all your data using your existing business intelligence tools. It is optimized for datasets 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.
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 EMR
Amazon EMR is used in a variety of applications, including log analysis, web indexing, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics. Customers launch millions of Amazon EMR clusters every year.
Snowflake eliminates the administration and management demands of traditional data warehouses and big data platforms. Snowflake is a true data warehouse as a service running on Amazon Web Services (AWS)—no infrastructure to manage and no knobs to turn.
See all alternatives

Treasure Data's Stats

- No public GitHub repository available -

Treasure Data's Followers
18 developers follow Treasure Data to keep up with related blogs and decisions.
Yuto Tachibana
Pete Doyle
Trang Pham
Kennedy Campbell
Chris Winsor
Kyle Prifogle
Abdullah Cetin CAVDAR