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.
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.
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.
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).
Query Methods: Traverser and graph navigation API, predicate language qualification, path pattern matching.
Parallel query support.
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.
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.
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.
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.
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:
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.