We provide expertise for the full lifecycle of your databases, leveraging over more than 20 years experience in database infrastructures.

We cover the following areas of expertise :

  • Database design
  • Performance tuning
  • Migration (including migration to Cloud)
  • Upgrade
  • Audit Services

 

 

 

postgresql

In a nutshell :

  • 8.x & 9.x
  • Upgrade and migration
  • Cloud IaaS deployment :¬† Amazon EC2, Microsoft Azure, Google Cloud
  • Cloud DBaaS : Amazon RDS, Alven, EDB Postgres Plus
  • Pgpool-II (HA & load balancing.)

In a nutshell:oracle

  • 9i, 10g, 11g, 12c
  • on-premise or on the cloud : DBaaS (Amazon RDS, Oracle Cloud).
  • Real Application Clusters (RAC) 11g+
  • Dataguard
  • Solaris, Linux, IBM AIX and MS Windows.

 

In a nutshell :mysql

  • Mysql 4.x, 5.x
  • MariaDB 10.0, 10.1, 10.2
  • On premise, or on IaaS (Amazon AWS, MS Azure, Google Cloud) and DBaaS (Amazon RDS, Oracle Cloud)

 

In a nutshell :

  • SQL Server 2008, 2012, 2014 and 2016
  • On premise or on the cloud : DBaaS/IaaS (Amazon RDS, Microsoft Azure)
  • Expertise with In-Memory OLTP features in SQL Server 2016 (Memory-optimized tables and Natively Compiled Stored Procedures) to achieve extremely low latency application performance.
Metric databases are rapidly becming very popular for dashboard and monitoring applications.We can help you integrate front-end applications such as Grafana with InfluxDB and implement metric collection in a variety of ways. We also help you integrate your metric collection agents with messaging infrastructures such as Apache Kafka or RabbitMQ.And of course, we support your deployments in-premise or on a Cloud infrastructure.

We have a good expertise deploying and maintaining InfluxDB database version 1.x

Our experience includes monitoring and IoT scenarios with the InfluxData TICK stack (Telegraf, InfluxDB, Chronograf and Kapacitor) as well as Grafana integration.

We support deployment to most popular IaaS providers.

We provide standard audit services for all the RDBMS and Metric Databases we support. The specific tools and techniques used may vary from system to system, but the methodology remains the same and is the fruit of years of experience delivering such services. Below you’ll find our service catalogue.

We help you improve the performance of your database system through a rigourous and scientific methodology. We start with the capture of baseline metrics in your system to characterize the load and identify bottlenecks. We give you recommendations in order to improve the overall performance of the system through configuration or hardware change (instance tuning).

 

At a second stage, we analyze the SQL statements and the application architecture in order to improve the application performance (SQL tuning and middleware). We work in a controlled test environment and deliver measured and verified recommendations for every test case.

We make a complete evaluation of the database system configuration, storage and administration processes in order to answer the following questions :

 

  • Is the database system coping well with the current workload ?
  • Will the database system be able to sustain the workload for the following X years ?
  • Can the database system grow smoothly ?
  • Are there any limitations of the current technology that I must be aware of ?
  • Is my database system future-proof ?
  • Are our Capacity Planning processes solid ?
  • Is my database system reliable ?
  • Is the database architecture appropriate for the current/future workload ?

This is a punctual evaluation of the system that requires a good understanding of the business processes it supports and is targeted at IT management in need of a risk assessment of the current infrastructure assets.

We perform a through analysis of the database system in order to identify security vulnerabilities and provide recommendations  to overcome them.

 

We investigate data privacy issues when required, in order to identify encryption requirements and regulatory compliance.

 

We perform a scalability analysis based on benchmarks and capacity models in order to evaluate how well a database system can scale under a certain level of concurrency.¬† This study is useful when evaluating new hardware investment for a database system and it’s important to have an idea of how the system will scale under a certain load.