Query Response TIME Comparison Nosqldb Mongodb with Sqldb Oracle

Penyimpanan data saat ini terdapat dua jenis yakni relational database dan non-relational database. Kedua jenis DBMS (Database Managemnet System) tersebut berbeda dalam berbagai aspek seperti per-formansi eksekusi query, scalability, reliability maupun struktur penyimpanan data. Kajian ini memiliki tujuan untuk mengetahui perbandingan performansi DBMS antara Oracle sebagai jenis relational data-base dan MongoDB sebagai jenis non-relational database dalam mengolah data terstruktur. Eksperimen dilakukan untuk mengetahui perbandingan performansi kedua DBMS tersebut untuk operasi insert, select, update dan delete dengan menggunakan query sederhana maupun kompleks pada database Northwind. Untuk mencapai tujuan eksperimen, 18 query yang terdiri dari 2 insert query, 10 select query, 2 update query dan 2 delete query dieksekusi. Query dieksekusi melalui sebuah aplikasi .Net yang dibangun sebagai perantara antara user dengan basis data. Eksperimen dilakukan pada tabel dengan atau tanpa relasi pada Oracle dan embedded atau bukan embedded dokumen pada MongoDB. Response time untuk setiap eksekusi query dibandingkan dengan menggunakan metode statistik. Eksperimen menunjukkan response time query untuk proses select, insert, dan update pada MongoDB lebih cepatdaripada Oracle. MongoDB lebih cepat 64.8 % untuk select query;MongoDB lebihcepat 72.8 % untuk insert query dan MongoDB lebih cepat 33.9 % untuk update query. Pada delete query, Oracle lebih cepat 96.8 % daripada MongoDB untuk table yang berelasi, tetapi MongoDB lebih cepat 83.8 % daripada Oracle untuk table yang tidak memiliki relasi.Untuk query kompleks dengan Map Reduce pada MongoDB lebih lambat 97.6% daripada kompleks query dengan aggregate function pada Oracle

Visual exploration and retrieval of XML document collections with the generic system X2

This article reports on the XML retrieval system X2 which has been developed at the University of Munich over the last five years. In a typical session with X2, the user first browses a structural summary of the XML database in order to select interesting elements and keywords occurring in documents. Using this intermediate result, queries combining structure and textual references are composed semiautomatically. After query evaluation, the full set of answers is presented in a visual and structured way. X2 largely exploits the structure found in documents, queries and answers to enable new interactive visualization and exploration techniques that support mixed IR and database-oriented querying, thus bridging the gap between these three views on the data to be retrieved. Another salient characteristic of X2 which distinguishes it from other visual query systems for XML is that it supports various degrees of detailedness in the presentation of answers, as well as techniques for dynamically reordering and grouping retrieved elements once the complete answer set has been computed

Towards an Efficient Evaluation of General Queries

Database applications often require to evaluate queries containing quantifiers or disjunctions, e.g., for handling general integrity constraints. Existing efficient methods for processing quantifiers depart from the relational model as they rely on non-algebraic procedures. Looking at quantified query evaluation from a new angle, we propose an approach to process quantifiers that makes use of relational algebra operators only. Our approach performs in two phases. The first phase normalizes the queries producing a canonical form. This form permits to improve the translation into relational algebra performed during the second phase. The improved translation relies on a new operator - the complement-join - that generalizes the set difference, on algebraic expressions of universal quantifiers that avoid the expensive division operator in many cases, and on a special processing of disjunctions by means of constrained outer-joins. Our method achieves an efficiency at least comparable with that of previous proposals, better in most cases. Furthermore, it is considerably simpler to implement as it completely relies on relational data structures and operators

Extending a multi-set relational algebra to a parallel environment

Parallel database systems will very probably be the future for high-performance data-intensive applications. In the past decade, many parallel database systems have been developed, together with many languages and approaches to specify operations in these systems. A common background is still missing, however. This paper proposes an extended relational algebra for this purpose, based on the well-known standard relational algebra. The extended algebra provides both complete database manipulation language features, and data distribution and process allocation primitives to describe parallelism. It is defined in terms of multi-sets of tuples to allow handling of duplicates and to obtain a close connection to the world of high-performance data processing. Due to its algebraic nature, the language is well suited for optimization and parallelization through expression rewriting. The proposed language can be used as a database manipulation language on its own, as has been done in the PRISMA parallel database project, or as a formal basis for other languages, like SQL