About

According to Gartner 80% of big data projects will fail, with the main reason being the human involvement required for data preparation and engineering, before being able to leverage these in a big data analytics platform. This problem is fundamental and often a deterrent when starting a big data project. Many of the existing platforms provide a large set of options which, however, cost a lot and are not used in their entirety by their customers. For this, we have designed and we are currently implementing the DBLabs platform that provides a very easy and mainly fast way to create a big data infrastructure by providing a set of tools and subsystems to automate the process of Extract Transform Load (ETL) pipelines and Change Data Capture (CDC).

Solution & Product

DBLabs Platform has the following applications and subsystems: 1. Data-Source Configurator: an application that allows the configuration of data sources. To keep the footprint as small as possible, we currently support Oracle, Postgres, MySQL and MongoDB which are more than 80% of the current database installations. 2. ETL pipeline and CDC engine: An efficient, optimized, small-footprint, cluster enabled engine for running pipelines and keeping source data synchronized with the big-data backend. 3. Big Data Back-End Configurator: One-click Apache Spark cluster installer on AWS, Google Cloud or on-premise. 4. Platform Orchestrator: API and command prompt for running all the above in one step. Also it is used for provisioning and monitoring. All configurators can run stand-alone and create their correspondent elements, but they can also export their tasks in a unified editable descriptive schema to run as one process from the platform orchestrator.

Innovation & Scalability

We are developing DBLabs Platform, a small and fast data integration platform. DBLabs Platform enables customers to easily and quickly acquire a big-data infrastructure to start running data analytics. Due to the small footprint and optimized CDC techniques, which is the main problem in such infrastructures, our platform generally provides much better response times than other systems. DBLabs Platform will also be offered at very competitive prices because it can meet the needs of a big-data infrastructure without additional and often unnecessary features. In addition, the implementation of Smart Adaptive CDC is in an experimental stage, which will be used for trend-analysis and can be automatically modified with Machine Learning procedures that will be applied on the data that will result from the analytics. Our unique value proposition is “Start fast, continue faster”.

Traction & achievements

Q1 2014 - DBLabs founded as a General Partnership Company to offer solutions on design and implementation of large scale applications and big data systems. Q2 2017 - Changed its legal entity to Single Member Private Company Q2 2020 - Utilizing our many years of experience, it was decided to move from the provision of services to the production and supply of products so that sales can be scaled up to a much larger customer base. The creation of DBLabs Platform will allow us to address and support many more customers worldwide. For the time being, we have chosen to grow organically at least until our platform can go public. Q4 2023 - Our first product release is expected to go public

Team & Why Us

- Panagiotis Xiros, CTO, Electrical Engineer NTUA, - Team of 3 highly experienced IT professionals working as freelancers

Funding Needs

For the time being, we have chosen to grow organically at least until our platform can go public.