Examples of using Dynamodb in English and their translations into Ukrainian
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Developing with DynamoDB.
DynamoDB uses the Paxos algorithm to elect leaders.
You can work with an array of databases, including NoSQL and DynamoDB.
DynamoDB uses both hashing and B trees to manage data.
In practice, this is where DynamoDB trades consistency for availability.
DynamoDB users issue queries directly to their indices.
A primary keycan also feature a second attribute, which DynamoDB calls the table's“sort key.”.
With DynamoDB, Amazon also offers its own NoSQL database, of course.
Utilize database services,such as Amazon Relational Database Service(RDS) and Amazon DynamoDB.
DynamoDB uses JSON for its syntax because of its ubiquity in the development community.
Just like indexing systems in the relational model, DynamoDB demands that any updates to a table be reflected in each of the table's indices.
DynamoDB affords the user two options when issuing a read: consistent and eventually consistent.
The name attempted to label the emergence of an increasing number of non-relational, distributed data stores,including open source clones of Google's Bigtable/MapReduce and Amazon's DynamoDB.
DynamoDB was announced by Amazon CTO Werner Vogels on January 18, 2012[5] and is presented as an evolution of Amazon SimpleDB solution.
Instead, a package containing the required tasks has to be created and uploaded(usually) to an S3 bucket andAWS is instructed(via Amazon Kinesis, DynamoDB or SQS) to run it when an event is triggered.
DynamoDB differs from other Amazon services by allowing developers to purchase a service based on throughput, rather than storage.
This essentially makes the instances stateless, all the incoming andoutgoing data needs to be stored by external means(usually via S3 or DynamoDB, inbound connections to the instances is disabled).
Languages and frameworks with a DynamoDB binding include Java, JavaScript, Node. js, Go, C. NET, Perl, PHP, Python, Ruby, Haskell, Erlang, Django, and Grails.[13].
A large message can be split into multiple segments that are sent separately,or the message data can be stored using Amazon Simple Storage Service(Amazon S3) or Amazon DynamoDB with just a pointer to the data transmitted in the SQS message.
DynamoDB periodically takes snapshots of these two data structures and stores them for a month in S3 so that engineers can perform point-in-time restores of their databases.
Dynamo had a multi-master designrequiring the client to resolve version conflicts and DynamoDB uses synchronous replication across multiple datacenters[4] for high durability and availability.
To prevent data loss, DynamoDB features a two-tier backup system of replication and long-term storage.[12] Each partition features three nodes, each of which contains a copy of that partition's data.
Amazon engineers avoided Dynamo originally due to engineering overheads like provisioning and managing partitions and nodes.[1]In response, the DynamoDB team built a service it calls AutoAdmin to manage a database.[2] AutoAdmin replaces a node when it stops responding by copying data from another node.
Like in relational systems, DynamoDB updates indices automatically on addition/update/deletion, so you must be judicious when creating them or risk slowing down a write-heavy database with a slew of index updates.
If Auto Scaling is enabled, then the database will scale automatically.[8] Additionally,administrators can request throughput changes and DynamoDB will spread the data and traffic over a number of servers using solid-state drives, allowing predictable performance.[2] It offers integration with Hadoop via Elastic MapReduce.
A DynamoDB table features items that have attributes, some of which form a primary key.[10] Whereas in relational systems, an item features each table attribute(or juggles“null” and“unknown” values in their absence), DynamoDB items are schema-less.
While a typical relational system would convert the SQL query to relational algebra and run optimization algorithms, DynamoDB skips both processes and gets right to work.[1] The request arrives at the DynamoDB request router, which authenticates--“Is the request coming from where/whom it claims to be?”-- and checks for authorization--“Does the user submitting the request have the requisite permissions?”.
In DynamoDB, there is no query optimizer, and an index is simply another table with a different key(or two) that sits beside the original.[1] When a developer creates an index, she creates a new copy of her data, but only the fields that she specifies get copied over(at a minimum, the fields that she indexes on and the original table's primary key).
Amazon DynamoDB is a fully managed proprietary NoSQL database service that supports key-value and document data structures[2] and is offered by Amazon. com as part of the Amazon Web Services portfolio.[3] DynamoDB exposes a similar data model to and derives its name from Dynamo, but has a different underlying implementation.
DynamoDB handles this using a service it calls the“log propagator,” which subscribes to the replication logs in each node and sends further Put, Update, and Delete requests to indices as necessary.[1] Because indices result in substantial performance hits for write requests, DynamoDB allows a user at most five of them on any given table.