BangDB
 | |
| Producer | Sachin Sinha (India) |
|---|---|
| History | Founded 2012 |
| Languages | C/C++ |
| Access | |
| Providers | Iqlect Software Solutions |
| Coverage | |
| Format coverage | NoSQL, Database |
| Links | |
| |
BangDB is a NoSQL database written in C/C++ from scratch to scale out applications suitable for heavy lifting.[1][2] It is a multi-flavored database available as BangDB Embedded, BangDB Server, Data Fabric and Elastic Cache.[3] It is an embedded database for transactional key value data which supports full ACID (Atomicity, Consistency, Isolation and Durability) by implementing optimistic concurrency control with parallel verification for high performance and concurrency and is downloadable via a BSD License.[4][5]
BangDB was developed and authored by Sachin Sinha in 2012.[2] It has its own buffer pool, write ahead log with crash recovery system and provides users with many configuration to control the execution environment including the memory budget.[6]
History[edit]
BangDB was developed in 2011 and released its first beta version in 2012 November.[7] BangDB 0.1 was released with few simple features such as key- value store DB with opaque data, support for Btree + extHash, get, put, delete and simple scan, write-ahead log and buffer pool.[8] When it was first developed, it was mostly used for fast key access especially for a small size data.[7]
In 2014, BangDB 0.9 was released which included features like replication, support for multiple table types and index support. Currently BangDB 1.5 is the recent version for BangDB-embedded and server.[9]
BangDB is not fully open-source. It is offered as binaries under BSD 3 licence for free which has a limited usage constrain.[10]
BangDB, which is a part of IQLECT Software Solutions[11] was backed by Exfinity ventures in the year 2014.[12][13]
Architecture[edit]
The architectural objectives while designing the BangDB were:
- The Flexibility - key-value store in various forms
- The performance and scalability
- The robustness and reliability.
BangDB - Embedded[edit]
BangDB Embedded version is part of the BangDB family and a high level architecture consists of three main important components of the Database.[14][15]
- The Access Methods or indexes
- The Buffer Pool and management, and
- The Write Ahead Log
BangDB-Server[edit]
In this flavour, BangDB runs as network service and clients access it over the network. This model is good for sharing data with multiple apps or instances of an app. The typical use case for this flavour is cache on top of the database, a network data store etc.
The architecture of BangDB follows a form of Staged Event-Driven Architecture (SEDA) which suits a highly concurrent network server. The server is stage driven and with a number of stages available as configurable parameter. This makes the server well-conditioned even with increasing loads and connections in a highly stressed scenario.[15][16]
Performance[edit]
BangDB performs well for both read and write in save mode or non-save mode (as a cache). BangDB implements its own buffer pool with semi-adaptive page prefetch and performed well even with billion keys insert when compared with other NoSQL DBS.[17]
BangDB also implements write ahead log which append only and so it avoids random seeks by optimizing the disk writes.[17]
The BangDB server runs on Linux (Supports Ubuntu, Debian, CentOS, Fedora, RedHat, and SUSE with an OS version 2.6 X onwards (32/64) bit).[18]
Differences with other database systems[edit]
Since BangDB is a NoSQL Database, it is not suitable for any relational database management systems (RDBMS) and cannot run SQL based queries. It is also said not to be suitable for heavy business intelligence queries and banking and financial DB structures.
But BangDB is time and storage efficient and has high processing speed for log data analysis, Streaming data performed in a distributed cluster environment.[19]
See also[edit]
- NoSQL
- C
- C++
- Big data
- Data analysis
- Document-oriented database
- Key–value database
- Multi-model database
References[edit]
- ↑ "Big data firm Iqlect gets $2.5 million in Bridge Round". indiatimes.com. Retrieved 20 August 2020. Unknown parameter
|url-status=ignored (help) - ↑ 2.0 2.1 "A deep dive into NoSQL: A complete list of NoSQL databases". Big Data Made Simple. 2014-07-21. Retrieved 20 August 2020.
- ↑ Vivek, Tiwari; Basant, Tiwari; Singh, Thakur, Ramjeevan; Shailendra, Gupta (2016-07-22). Pattern and Data Analysis in Healthcare Settings. IGI Global. ISBN 978-1-5225-0537-2. Search this book on
- ↑ "Iqlect | About - Elastic BigData Space". bangdb.com. Retrieved 20 August 2020.
- ↑ "BangDB - NoSQL for Real Time Performance". bangdb.com. Retrieved 20 August 2020.
- ↑ "IQLECT provides insights in real-time, makes data analytics affordable". The Financial Express. 2017-03-22. Retrieved 20 August 2020.
- ↑ 7.0 7.1 "Bangdb System Properties". db-engines.com. Retrieved 20 August 2020.
- ↑ "LIST OF NOSQL DATABASE MANAGEMENT SYSTEMS". no-sql database. Retrieved 20 August 2020. Unknown parameter
|url-status=ignored (help) - ↑ "Google Groups". groups.google.com. Retrieved 20 August 2020.
- ↑ "Bangdb System Properties". db-engines.com. Retrieved 20 August 2020.
- ↑ "IQLECT: Predictive & real-time data analytics to easily". QuickBooks. 2016-05-16. Retrieved 20 August 2020.
- ↑ "Exfinity ventures startups portfolio". 2014. Retrieved 20 August 2020. Unknown parameter
|url-status=ignored (help) - ↑ Exfinity Ventures, Exfinity Ventures. "Ventureast and Exfinity back analytics startup IQLECT in bridge round". Vcc Circle. Retrieved 20 August 2020. Unknown parameter
|url-status=ignored (help) - ↑ "BangDB Embedded — Национальная библиотека им. Н. Э. Баумана". ru.bmstu.wiki. Retrieved 20 August 2020.
- ↑ 15.0 15.1 "BangDB Resources". bangdb.com. Retrieved 20 August 2020.
- ↑ "Performance Data For LevelDB, Berkley DB And BangDB For Random Operations". highscalability.com. 29 November 2012. Retrieved 20 August 2020. Unknown parameter
|url-status=ignored (help) - ↑ 17.0 17.1 "BangDB 2.0 API". bangdb.com. Retrieved 20 August 2020.
- ↑ "BangDB NoSql". bangdb.com. Retrieved 2020-02-25.
- ↑ Bridgeport University, Scholarworks. "Web Search and Browser Log analysis using BangDB for Decision Support" (PDF). Brigeport university scholarlinks. Retrieved 20 August 2020. Unknown parameter
|url-status=ignored (help)
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