Audience
Developers searching for a key-value database solution
About KeyDB
KeyDB maintains full compatibility with Redis modules, API and protocol. Seamlessly drop in KeyDB and maintain full compatibility with your existing clients, scripts and configurations. Multi-Master mode uses a single replicated dataset across many nodes to serve both read and write operations Nodes can be replicated cross-region to offer submillisecond latencies to local clients. Cluster mode allows unlimited read and write scaling by splitting the dataset across shards. This allows unlimited scaling, and also support high availability through replica nodes. KeyDB offers new community driven commands that enable you to do more with your data. Add your own commands and functionality using JavaScript with the ModJS module. ModJS lets you write functions in javascript that can in turn be called directly by KeyBD. The example to the left shows and example of a javascript function that would be loaded with the module. It can then be called directly from your client.
Apache Accumulo
With Apache Accumulo, users can store and manage large data sets across a cluster. Accumulo uses Apache Hadoop's HDFS to store its data and Apache ZooKeeper for consensus. While many users interact directly with Accumulo, several open source projects use Accumulo as their underlying store. To learn more about Accumulo, take the Accumulo tour, read the user manual and run the Accumulo example code. Feel free to contact us if you have any questions. Accumulo has a programming mechanism (called Iterators) that can modify key/value pairs at various points in the data management process. Every Accumulo key/value pair has its own security label which limits query results based off user authorizations. Accumulo runs on a cluster using one or more HDFS instances. Nodes can be added or removed as the amount of data stored in Accumulo changes.
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Redis
Redis Labs: home of Redis.
Redis Enterprise is the best version of Redis. Go beyond cache; try Redis Enterprise free in the cloud using NoSQL & data caching with the world’s fastest in-memory database.
Run Redis at scale, enterprise grade resiliency, massive scalability, ease of management, and operational simplicity. DevOps love Redis in the Cloud. Developers can access enhanced data structures, a variety of modules, and rapid innovation with faster time to market.
CIOs love the confidence of working with 99.999% uptime best in class security and expert support from the creators of Redis.
Implement relational databases, active-active, geo-distribution, built in conflict distribution for simple and complex data types, & reads/writes in multiple geo regions to the same data set.
Redis Enterprise offers flexible deployment options, cloud on-prem, & hybrid. Redis Labs: home of Redis. Redis JSON, Redis Java, Python Redis, Redis on Kubernetes & Redis gui best practices.
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Azure Cache for Redis
As traffic and demands on your app increase, scale performance simply and cost-effectively. Add a quick caching layer to the application architecture to handle thousands of simultaneous users with near-instant speed—all with the benefits of a fully managed service. Superior throughput and performance to handle millions of requests per second with sub-millisecond latency. Fully managed service with automatic patching, updates, scaling, and provisioning so you can focus on development. RedisBloom, RediSearch, and RedisTimeSeries module integration, supporting data analysis, search, and streaming. Powerful capabilities including clustering, built-in replication, Redis on Flash, and availability of up to 99.99 percent. Complement database services like Azure SQL Database and Azure Cosmos DB by enabling your data tier to scale throughput at a lower cost than through expanded database instances.
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Azure Table Storage
Use Azure Table storage to store petabytes of semi-structured data and keep costs down. Unlike many data stores—on-premises or cloud-based—Table storage lets you scale up without having to manually shard your dataset. Availability also isn’t a concern: using geo-redundant storage, stored data is replicated three times within a region—and an additional three times in another region, hundreds of miles away. Table storage is excellent for flexible datasets—web app user data, address books, device information, and other metadata—and lets you build cloud applications without locking down the data model to particular schemas. Because different rows in the same table can have a different structure—for example, order information in one row, and customer information in another—you can evolve your application and table schema without taking it offline. Table storage embraces a strong consistency model.
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Integrations
Company Information
KeyDB
Founded: 2018
Canada
keydb.dev/
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