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It wasn't very good for applications in which the entire data store needed to be transversed to create a report. This database model was very good for applications that stored and retrieved individual data items. Small files containing the index data would be developed that pointed back to where the rest of the "record" could be retrieved. This meant that data could be retrieved in sorted order without an explicit sort process.
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This approach to databases was somewhat similar to the navigational database model, but the data was stored in the indexes themselves. This program would make database queries that could never be satisfied, so that all the processing power of the host system would be consumed following links back and forth and up and down the mesh.
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I am aware of a situation in which a malicious developer, who was planning to leave the company, created a program that exploited a badly designed mesh. Some described this as an "upside-down tree" in which each record was linked to one or more owners and, potentially, other data items in a "mesh." While powerful, this approach was hard to understand and quite complex. This database model made it possible for multiple records to be linked to multiple owner records and vice-versa.
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A Data Manipulation Language (DML) was used by developers to give commands to the database, allowing programs to store, retrieve and update data. Without going into minute detail, the committee developed the concept of a Data Description Language (DDL) that was used to define the items that were to be stored and the relationships between and among them. In 1959, a consortium - the Committee on Data System Languages - was formed to both guide the development of a standard programming language and the development of a standard way to store "lists." The COBOL language was one of this committee's projects, and a "network database" was the result of its work on a standard way to store and retrieve data. If backup procedures didn't capture all the indices, IT staff would be forced to first discover that the index was missing, then run through a procedure to re-create it. Another challenge was restoring this type of database after a system crash. One challenge when one or more indices became corrupted was uncovering when the corruption happened, and fixing all updates to the main data file that may have been done erroneously. Once this issue was discovered, it was fairly straightforward to go through the data file and recreate the corrupted index. Unfortunately, it also was easy for the indexes and main data file to get out of synchronization. I used this approach for a hospital information system on a system that only had 16KB of main memory and three 6MB disks. This approach was fairly simple and easy to implement on what would be considered tiny systems today. This was called an "Indexed sequential file." Purists would point out that this really can't be considered a true database, even though many early transactional systems used this approach for data storage. Later, the index files were brought back into the data file. The indices were kept sorted in order so that the data file could be read in order, based on any of the indices. Applications could search one of the indices to find the needed record, then go to the data file and jump directly to the needed record. The index files contained a search field and a record number in the data file. It was made up of a number of separate files that contained indices, and a single file that contained the actual data. The earliest approach to constructing a useful data store that would allow applications to find records based upon a number of criteria was a navigational database. Now we see NoSQL databases becoming popular. Another was developed by the Committee on Data System Languages, and was known both by the name "CODASYL database" and "Network database." Yet another approach was known as a "Key/Value database," which was used both in MUMPS and the PICK systems. One approach was called a navigational database. (The following list certainly can't be considered comprehensive): Various Database Approaches I can recall many approaches that were widely used. Reviewing the history of databases, we quickly see that there have been many different approaches applied to address developer needs to store and retrieve different types of data. I was told that "We are working on the native multi-model idea, meaning that we found a way to efficiently combine three data models (key/value, documents, graphs) into one NoSQL database core and let users access their data with one declarative query language: AQL." A representative of ArangoDB reached out to present what the company thinks is a new idea.