What is a columnar database?

Question

I have been working with warehousing for a while.

I am intrigued by Columnar Databases and the speed they can offer for finding data.

I have a frequent question:

• How do columnar databases work?
• How do they differ from relational databases?

Answer 1

How do columnar databases work?
A columnar database is a concept, not a specific architecture / implementation. In other words, there is no concrete description of how these databases work; indeed, some of them are based on a traditional, row-oriented DBMS, simply storing information in tables with one (or rather two) columns (and adding the necessary level to access the column data in a simple way).

How do they differ from relational databases? They usually differ from traditional (row-oriented) databases in regards to ...

• performance...
• storage requirements ...
• ease of changing the circuit ...

... in specific cases of using a DBMS .
In particular, they offer advantages in the areas mentioned when a typical use is to calculate cumulative values ​​in a limited number of columns, as opposed to trying to get all / most columns for a given object.

Is there a trial version of the columnar database that I can install for the game? (I am on Windows 7) Yes, there is a commercial, free and also open version of columnar databases. See the list at the end of the Wikipedia article for a starter.
Remember that some of these implementations were introduced to address a specific need (say, very small footprint, highly compressible data distribution or emulation of a spare matrix, etc.) instead of providing a universal DBMS with a general purpose.

Note. The remark about the "single targeting" of several columnar DBMSs is not a criticism of these implementations, but rather indicates that such an approach for DBMSs departs from the more "natural" (and, of course, more widely used) approach to storing records. As a result, this approach is used when the row-oriented approach is not satisfactory, and therefore tends to a) target a specific purpose b) receive less resources / percent than work on General Purpose, Tested and Verified ", a tabular approach.

Tentatively, the Entity-Attribute-Value (EAV) data model may be an alternative storage strategy that you might want to consider. Despite the Columnar DB model different from the “clean” one, EAV shares several characteristics of the DB columns.

Answer 2

How do columnar databases work? The defining concept of column storage is that table values ​​are stored adjacent to a column. Therefore, the classic table supplier from CJ Date of supplier and spare parts:

SNO STATUS CITY SNAME --- ------ ---- ----- S1 20 London Smith S2 10 Paris Jones S3 30 Paris Blake S4 20 London Clark S5 30 Athens Adams 

will be stored on disk or in memory like this:

 S1S2S3S4S5;2010302030;LondonParisParisLondonAthens;SmithJonesBlakeClarkAdams 

This is different from the traditional rowstore, which stores data more like this:

 S120LondonSmith;S210ParisJones;S330ParisBlake;S420LondonClark;S530AthensAdams 

From this simple concept, all the fundamental differences in performance, for better or worse, arise between column storage and row storage. For example, column storage will succeed when performing aggregations such as totals and averages, but inserting a single row can be expensive, while the opposite is true for row stores. This should be apparent from the diagram above.

How do they differ from relational databases? A relationship database is a logical concept. A columnar database or column store is a physical concept. Thus, the two terms are not comparable in any significant sense. Collided DMBSs can be relational or not, just like row-oriented DBMSs can more or less be tied to relational principles.

Answer 3

I would say that the best candidate for understanding column oriented databases is HBase ( Apache Hbase ) validation . You check the code and study further to find out about the implementation.

Answer 4

Product Information. This can help. They were supposed to display products in a Google search.

http://www.vertica.com/

http://www.paraccel.com/

http://www.asterdata.com/index.php

Answer 5

In addition, Columnar DBs have built-in proximity to data compression, and the loading process is unique. Here's an article I wrote in 2008 that explains a little more.

You might also be interested in the new IDC Carl Olofson report on third-generation DBMS technology. It discusses columnar, etc. If you are not an IDC client, you can get it for free on our website. He also hosts a webinar on June 16 (also on our website).

(By the way, one comment above contains asterdata list, but I don’t think they are columnar.)

Answer 6

kx is another column database, for example, used in the financial sector. True, the last time I got a license in the amount of $ 50,000. No optimization is required, there is no need for an index, because kx has powerful operators (matlab equivalents:. .* , kron , bsxfun , ...).

Answer 7

To understand what a column-oriented database is, it is best to compare it with a row-oriented database.

String databases (for example, MS SQL Server and SQLite) are designed to efficiently return data for the entire string. He does this by storing all the column values ​​of the row together. String databases are well suited for OLTP systems (such as retail and financial transactions).

Column- oriented databases are designed to efficiently return data for a limited number of columns. He does this by storing all the column values ​​together. The two widely used column-oriented databases are Apache Hbase and Google BigTable (used by Google for search, analysis, maps, and Gmail). They are suitable for large data projects. A column-oriented database will outperform read operations in a limited number of columns, but a write operation will be expensive compared to row-oriented databases.

More details: https://en.wikipedia.org/wiki/Column-oriented_DBMS

Answer 8

Columnar databases are widely used in analytics and BI. According to the wiki . By storing data in columns rather than rows, the database can more accurately obtain the data needed to respond to a query, rather than scanning and discarding unwanted data in rows. They are well suited for OLAP-like data warehouse workloads. According to an empirical article, organizations often use a row-oriented database running in the backend and a columnar database for foreground business needs.