BlobCity DB

BlobCity DB

An open-source multi-model database, designed to meet a wide variety of data storage, fast data retrieval and analytics requirements.

Get Started    

A better DataLake than Hadoop

We all use Hadoop as the de-facto choice for a DataLake. Why so, because we can throw any data at it. But in reality we cannot throw any data at it. Most of our data is convertible to plaintext, and Hadoop accepts only plaintext. We convert all our data into plaintext and then throw it into Hadoop.

However does plain text storage in Hadoop address any problem? Yes, it does allow you to store all your organisational data in one place. But because your JSON & XML went in as plain text, analysing it within Hadoop now requires excess code.

Feature Comparison

Feature
Hadoop
BlobCity DB

Distributed

Yes

Yes

Plaintext data

Yes

Yes

JSON data

No

Yes

XML data

No

Yes

PDF, Word, Excel data

No

Yes

ACID Compliance

No

Yes

Stored Procedures

Yes
(Map-Reduce Only)

Yes
(Java + Scala)

In-memory Processing

No
(Possible with Spark)

Yes
(Built-in engine)

Future proof your DataLake

Using BlobCity as a DataLake futures proofs your DataLake infrastructure. With native support for 17 different formats of data and option of moving part data to in-memory for faster analytics, BlobCity strikes the right balance between features, performance, customer needs and cost effectiveness.

New systems may bring in data in newer formats that are currently not anticipated, and BlobCity will most likely and readily accept that format. This means new systems can report data to your DataLake with minimalistic integration effort.

If some queries are performing slower due to limitation of disk IO, the corresponding data can be instantly moved into memory to allow high speed and real-time analytics over such data.

A better DataLake than Hadoop


Suggested Edits are limited on API Reference Pages

You can only suggest edits to Markdown body content, but not to the API spec.