Although the domain of the site is a .com, SQLPAC is not a commercial corporation and has no profit-making purpose. Nothing to sell.

SQLPAC is the acronym for a "slogan": SQL for Administrators & Designers (Concepteurs in French). But not only SQL… One goal : knowledge sharing and feedbacks.

Created in 2003, the SQLPAC site was initially built to group some quick guides (command lines, usages…) and over time, articles and tutorials are published about the products of 4 database vendors.

SQLPAC is first and foremost a web site for french speakers, because we must not forget the readers who may have difficulties in English. Articles, tutorials, toolboxes and feedbacks on transactional and decision-making database systems are published. The explored domains extend from administration to optimization and tuning through maintenance, replication and high availability.

Some articles are translated into English. Audience measurement with Google Analytics governs the choice to translate an article. Any help is welcome, because it is very difficult to translate an article when you are not English or bilingual. An english colleague told us frankly and openly many years ago : "your emails in English ? we understand the meaning or the purpose, but…, an english speaker would have written differently…"

Many articles within SQLPAC web site are the result of an active partnership with software vendors in the beta phases of innovative products meeting strong business needs :

  1. 2005 Sybase Real Time Data Services for IBM MQ Series
    Real time communication between databases and message queueing systems is implemented with the component Sybase RTDS for IBM MQ Series.
  2. 2008 Sybase IQ
    Sybase IQ is introduced in the studies portfolio. It was the most advanced column storage engine at that time. This engine has changed mind spirits about building reports and querying data on an exploding volume of data.
  3. 2010 Sybase Real Time Loading for IQ
    Real time replication from Sybase Replication Server to Sybase IQ.
  4. 2017 Microsoft SQL Server 2017 on Linux
  5. 2019 MariaDB ColumnStore
  6. 2020 InfluxDB v2 (Time Series)

SQL, but not only SQL…

Languages, Operating systems…

logo PHP logo Python logo R logo OpenLDAP logo Tux Linux

A database is designed to be efficiently queried and is installed on an operating system, so some topics about systems (Unix, Linux. ..), development with clients (PHP, Python, C#…) or transversal technologies (LDAP directories for authentication…) are also published. Understanding the client layers of databases and using them effectively is often underestimated.


Logo Google Logo Google Analytics

Google has become over time a favorite topic of SQLPAC too. Google is not a database engine per se but its innovative and powerful technologies used within SQLPAC web site deserve some articles (SEO and indexing optimization, Google Analytics, custom Google search engines…).


Logo GIMP Logo HTML Logo CSS Logo Javascript Logo Apache

More incongruous within SQLPAC web site, some articles about image processing with GIMP, development in HTML, Javascript and CSS, or administering an Apache HTTP Server are published. The publication of these topics is often directly related to the development of SQLPAC web site and serves mainly as a tutorial and help (a database administrator does not remove a background color in an image every day…). If it can help, good.


The current roadmap and the topics in progress or in preparation, here they are summarized below with thumbnails, much better than a long speech, thumbnails in which the SQL and the NoSQL technologies are mixed intimately voluntarily :

Our convictions: many times on social networks, historical relational databases and the SQL language are now called "old school" compared to emerging BigData technologies, more adapted obviously for huge volume growths. Strangely, this perception reminds us the same comments that we could read or hear when object-oriented languages ​​appeared, or earlier when the new client / server technologies arrived among the mainframes (COBOL, IBM…) . The two ecosystems, relational databases and BigData, must not be technically and from a skills point of view compartmentalised as they complement each other and must communicate and interact together, in real time if possible. This is already the case, for examples MariaDB Server is able to communicate in real time with Kafka messaging system, Microsoft SQL Server with Hadoop since version 2016, SAP Sybase Replication Server can now replicate data in real time to Hive, and many other examples…

With our convictions, let’s analyze how relational SGBD and BigData ecosystems can interact together. We mustn’t perceive them as antithetical systems.