high_scalability high_scalability-2010 high_scalability-2010-961 knowledge-graph by maker-knowledge-mining
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Introduction: This is a guest post by Frédéric Faure (architect at Ysance ), you can follow him on twitter . Data storage has always been one of the most difficult problems to address, especially as the quantity of stored data is constantly increasing. This is not simply due to the growing numbers of people regularly using the Internet, particularly with all the social networks, games and gizmos now available. Companies are also amassing more and more meticulous information relevant to their business, in order to optimize productivity and ROI (Return On Investment). I find the positioning of SQL and NoSQL (Not Only SQL) as opposites rather a shame: it’s true that the marketing wave of NoSQL has enabled the renewed promotion of a system that’s been around for quite a while, but which was only rarely considered in most cases, as after all, everything could be fitted into the « good old SQL model ». The reverse trend of wanting to make everything fit the NoSQL model is not very p
sentIndex sentText sentNum sentScore
1 A so-called SQL database is a structured relational storage system: “structured” means that an ensemble of attributes (columns) which will contain data (values) will correspond to a single or composite key. [sent-8, score-0.4]
2 A relationship is therefore established between these two tables and repetition of the same information in all the lines of the table is avoided. [sent-11, score-0.343]
3 Functional features are structured and modeled in the database… NoSQL is a structured database which enables access to stored data via a simple key. [sent-12, score-0.394]
4 It is therefore possible to execute SQL-type conditional requests and thus recover information or compile statistics by using WHERE clauses. [sent-26, score-0.41]
5 The write performances will be unitarily better with a NoSQL tool (as opposed to a SQL tool with an equivalent data set on a key-value(s) model), but it doesn’t do everything, as we will see later. [sent-29, score-0.398]
6 I’m deliberately not talking about cache systems at this point, even if the cache would be genuinely useful in this case for the elements which tend to be accessed in read, therefore for the SQL part. [sent-30, score-0.507]
7 If it doesn’t have relational databases with integrated business / functional notions (object modelisation), I wouldn’t even attempt to touch it with a barge pole. [sent-33, score-0.378]
8 This enables Memcached to be deleted and you therefore no longer have to manage the problem of data inconsistency between Memcached and the MySQL database, and you can make the best use of the RAM by only using the InnoDB buffer pool. [sent-48, score-0.404]
9 This means, therefore, that if the data don’t all (or nearly all) fit into the memory and that you must therefore create a reasonable number of disk accesses (read, or, even worse… write! [sent-55, score-0.437]
10 Don’t underestimate the importance of the functional analysis of the data that you will put in the NoSQL database either. [sent-79, score-0.246]
11 A cache will always be useful, no matter what type of database you’re using (SQL or NoSQL) and will always be used in the case of data accessed essentially in read. [sent-103, score-0.274]
12 NoSQL databases often work in memory and even offer full memory modes (like a cache but without TTL and with the possibility of replication on a slave which writes to disk). [sent-104, score-0.314]
13 However, even with a cache that is sufficiently dimensioned, the requests still cost them processing time (CPU), bandwith, etc. [sent-106, score-0.246]
14 The purpose of a pure cache (with TTL hit management) in front will be to relieve the database, no matter which kind, of the burden of any read possible, in order to let it concentrate on the write requests or sending back the more dynamic/volatile data in read. [sent-107, score-0.426]
15 So, a cache can be placed equally in front of an SQL or a NoSQL base in order to economize resources. [sent-108, score-0.256]
16 As soon as disk accesses become necessary, whether because the dataset in read does not fit in memory or because there is a high number of writes, performance will be poorer, and a bottleneck will occur at the OS/hardware level via the disk IOs . [sent-115, score-0.242]
17 Don’t underestimate the importance of the functional specifications of the data that you will load into the NoSQL database, either. [sent-117, score-0.254]
18 In the HandlerSocket example, the point is above all to unify the data cache in a single location (the InnoDB buffer pool) in order to ensure the consistency of the data without necessarily compromising on the performance provided by a Memcached. [sent-122, score-0.332]
19 There is an interesting variety of NoSQL databases with specific functionalities, but be careful: having extra functionalities means less efficient response times than with the standard key-value(s). [sent-123, score-0.222]
20 Take for example the API « Table » of Tokyo Cabinet, which enables management of conditional requests, or even the geospatial functionalities of MongoDB. [sent-124, score-0.41]
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