Small Discussion about Mark Logic?

What is Mark Logic?

MarkLogic is an operational and transactional Enterprise NoSQL database that integrates data better, faster, with less cost.
MarkLogic is a single product that combines features of a highly distributed NoSQL database, a search engine, all with application services layered over the top.
In MarkLogic the search engine is part of the same product. Thus you don’t need to ‘bolt on’ a third party product with all the integration code and separate update schedules that implies. Also, MarkLogic uses the same underlying indexes for simple primary/secondary key fetching of documents (a la database access) as it does for use by the search engine. Thus MarkLogic is more frugal on disc requirements for indexes.

Everything in MarkLogic is stored as compressed binary trees – NOT as raw documents – not even simply as gzipped documents – so MarkLogic saves disc space over alternatives. MarkLogic storing documents with an average (say 5-15) range indexes will effectively use the same amount of disc space – for data plus indexes – as the raw document. This is part of our secret sauce, and the algorithms are patented.

Features

ACID Transactions
High Availability & Disaster Recovery
Certified Security
Write Once, Run It Anywhere

Benefits

Scalability
Bitemporal
Tiered Storage
Geospatial
Semantics
Real-Time Alerting

Video for Mark Logic Overview

Small Discussion About Berkeley DB?

What is Berkeley DB?

Berkeley DB (BDB) is a software library intended to provide a high-performance embedded database for key/value data. Berkeley DB is written in C with API bindings for C++, C#, Java, Perl, PHP, Python, Ruby, Smalltalk, Tcl, and many other programming languages. BDB stores arbitrary key/data pairs as byte arrays, and supports multiple data items for a single key. Berkeley DB is not a relational database.

BDB can support thousands of simultaneous threads of control or concurrent processes manipulate

Berkeley DB is a family of embedded key-value database libraries providing scalable high-performance data management services to applications. The Berkeley DB products use simple function-call APIs for data access and management

There are 3 implementations of Oracle Berkeley DB:

Oracle Berkeley DB - implemented in C
Oracle Berkeley JE - implemented in Java
Oracle Berkeley XML - implemented in C++

The Berkeley DB library is extremely portable. It runs under almost all UNIX and Linux variants, Windows, and a number of embedded real-time operating systems. It runs on both 32-bit and 64-bit systems. It has been deployed on high-end Internet servers, desktop machines, and on palmtop computers, set-top boxes, in network switches, and elsewhere. Once Berkeley DB is linked into the application, the end user generally does not know that there's a database present at all.

Video for Berkeley DB

https://www.youtube.com/watch?v=eQfr8RqOqj8

Small Discussion About C-Tree Database?

What is C Tree ACE?
c-treeACE is a cross-platform database engine developed by FairCom Corporation. Software developers typically embed the c-treeACE engine within the applications that they create and then deploy the application and engine together as an integrated solution.

The nature of c-treeACE allows it to be used in a range of products including: embedded systems that require limited disk and memory footprint and silent operation; shrink-wrap products developed by ISVs that require cross-platform support, minimal maintenance, and mass deployment; and enterprise systems that depend on performance and more precision control of database operations than a traditional enterprise database offers.

Two versions of the product are available. c-treeACE Express is freely available for development from FairCom's web site and supports only the client/server architecture. The client-side libraries are precompiled, making it easy to use for evaluation. c-treeACE Professional is licensed separately and supports all architectures and includes full source code for the client libraries and much of the source code for the server.

c-treeACE is one of few databases that specialize in making data locked into legacy database architecture available to modern APIs while minimizing time, resources and risks involved in modernization projects.

c-treeACE combines the benefits of NoSQL such as high performance, low latency and precise data access control, with the flexbility of SQL interfaces.

c-treeACE engine is a prime embodiment of a NoSQL, full ACID-compliant key-value database. If you are looking for NoSQL, you need look no farther than the c-treeACE database technology which many trust every day. Keeping with these times, you may notice NoSQL terminology appearing in our communications. Our veteran c-tree developers know we are referring to our powerful ISAM engine in use by customers every day for over 30 years.

Video for C Tree

https://www.youtube.com/watch?v=UX6t3-VZ_1k

Small Discussion About InfiniteGraph?

What is InfiniteGraph?
InfiniteGraph is an enterprise distributed graph database implemented in Java, and is from a class of NOSQL (or Not Only SQL) database technologies that focus on graph data structures. Developers use Infinitegraph to find useful and often hidden relationships in highly connected big data sets.

Benefits:

Distributed
Intuitive
Cost Effective
Powerful Navigation

Features:

API/Protocols: Java (core C++)
Graph Model: Labeled directed multigraph. An edge is a first-class entity with an identity independent of the vertices it connects.
Backup, including online incremental backup and full restore.
Concurrency: Update locking on subgraphs, concurrent non-blocking ingest.
Consistency: Flexible (from ACID to relaxed).
Distribution: Lock server and 64-bit object IDs support dynamic addressing space (with each federation capable of managing up to 65,535 individual databases and 10^24 bytes (one quadrillion gigabytes, or a yottabyte) of physical addressing space).
Processing: Multi-threaded.
Cloud enabled.
Query Methods: Traverser and graph navigation API, predicate language qualification, path pattern matching.
Parallel query support.
Visualization tool.
Schema: Supports schema-full plus provides a mechanism for attaching side data.
Transactions: Fully ACID.
Tinkerpop Blueprints and Gremlin support.
Talend output connector to InfiniteGraph.
Source: Proprietary, with open source extensions, integrated components, and third party connectors.
License Options: Flexible pricing and license options.
Platforms: Windows, Linux, and Mac with full interoperability.

Video for InfiteGraph

https://www.youtube.com/watch?v=BjaY62aVP08

Small Discussion About Firebase?

What is Firebase?

The Firebase Realtime Database is a cloud-hosted database. Data is stored as JSON and synchronized in realtime to every connected client. When you build cross-platform apps with our iOS, Android, and JavaScript SDKs, all of your clients share one Realtime Database instance and automatically receive updates with the newest data.

The Firebase Realtime Database lets you build rich, collaborative applications by allowing secure access to the database directly from client-side code. Data is persisted locally, and even while offline, realtime events continue to fire, giving the end user a responsive experience. When the device regains connection, the Realtime Database synchronizes the local data changes with the remote updates that occurred while the client was offline, merging any conflicts automatically.

The Realtime Database provides a flexible, expression-based rules language, called Firebase Realtime Database Security Rules, to define how your data should be structured and when data can be read from or written to. When integrated with Firebase Authentication, developers can define who has access to what data, and how they can access it.

The Realtime Database is a NoSQL database and as such has different optimizations and functionality compared to a relational database.

Firebase realtime database is a schemaless database in which the data is stored in JSON format. Basically the entire database is a big JSON tree with multiple nodes. So when you plan your database, you need to prepare the json structure in way that the data is accessible in easier way by avoiding nesting of child nodes.

Firebase provides great support when comes to offline data. It automatically stores the data offline when there is no internet connection. When the device connects to internet, all the data will be pushed to realtime database.

Video for what is Firebase?

https://www.youtube.com/watch?v=U5aeM5dvUpA

Small Discussion About Zope?

What is Zope?

The Zope Object Database (ZODB) is an object-oriented database for transparently and persistently storing Python objects. It is included as part of the Zope web application server, but can also be used independently of Zope.

Because ZODB is an object database:

no separate language for database operations
very little impact on your code to make objects persistent
no database mapper that partially hides the database.

Using an object-relational mapping is not like using an object database.
almost no seam between code and database.

The Zope Foundation is an organization that promotes the development of the Zope platform by supporting the community that develops and maintains the relevant software components. The community includes both open source software, documentation and web infrastructure contributors, as well as business and organization consumers of the software platform. It manages the zope.org websites, an infrastructure for open source collaboration.

Plone uses the ZODB database. The ZODB happily stores any Python object with any attributes — there is no need to write database schema or table descriptions as there is with SQL-based systems. If data models are described somehow the descriptions are written in Python, usually using zope.schema package.

Video for Zope

https://www.youtube.com/watch?v=vnZ6dj_1c14

Small Discussion About ArangoDB?

What is ArangoDB?

ArangoDB is a native multi-model database with flexible data models for documents, graphs, and key-values. Build high-performance applications using a convenient SQL-like query language or JavaScript extensions.

Multi-Model: Documents, graphs and key-value pairs — model your data as you see fit for your application.
Joins: Conveniently join what belongs together for flexible ad-hoc querying, less data redundancy.
Transactions: Easy application development keeping your data consistent and safe. No hassle in your client.

ArangoDB is to use the arangoimp command-line tool. arangoimp allows you to import data records from a file into an existing database collection.

ArangoDB provides scalable, highly efficient queries when working with graph data.The database uses JSON as a default storage format, but internally it uses ArangoDB's VelocyPack - a fast and compact binary format for serialization and storage.ArangoDB can natively store a nested JSON object as a data entry inside a collection. Therefore, there is no need to disassemble the resulting JSON objects.

Video for ArangoDB?

https://www.youtube.com/watch?v=on1l2pEEWnw

Discussion about Amazon Dynamo DB?

What is Amazon DynamoDB?
Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability. ... With DynamoDB, you can create database tables that can store and retrieve any amount of data, and serve any level of request traffic.

Amazon DynamoDB Accelerator (DAX) is a fully managed, highly available, in-memory cache that can reduce Amazon DynamoDB response times from milliseconds to microseconds, even at millions of requests per second.

Forrester Research positions Amazon Web Services in the Leaders Category of the Forrester Wave Big Data NoSQL, Q3. According to Forrester, Amazon DynamoDB is the most popular NoSQL cloud database. Learn why DynamoDB has proven to be a cost-effective NoSQL database solution for three organizations interviewed by IDC.

DynamoDB exposes performance metrics that helps provision it correctly and to keep applications using DynamoDB running smoothly:

Requests and throttling
Errors: ConditionalCheckFailedRequests, UserErrors, SystemErrors
Metrics related to Global Secondary Index creation

The DynamoDB Triggers feature integrates with AWS Lambda to allow a developer to code actions based on updates to items in a DynamoDB table, such as sending a notification or connecting a table to another data source. The developer associates a Lambda function, which stores the logic code, with the stream on a DynamoDB table. AWS Lambda then reads updates to a table from a stream and executes the function.

Video for DynamoDB

https://www.youtube.com/watch?v=ujWV3-m1pLo

Small Discussion about Mark Logic?

References

Your comment on this post:

Related Articles