Top 8 NoSQL Key Value Databases
Organizations have been using relational databases to overcome data anomalies and avoid reusing databases for new applications. However, the relational database model has failed to meet the increasing needs of database users in today’s big data world.
Many organizations are handling large volumes of data and operations that are difficult to manage without the right tools. This is a major challenge because relational databases cannot handle the challenges faced by modern applications. Also, relational databases cannot cope with the processing power of modern applications.
Luckily, NoSQL databases emerged to help database users solve the problems associated with the relational database model. These databases do not use SQL and have proven to be effective in managing numerous read and write operations and large datasets. There are different types of NoSQL databases and each one of them is effective in performing certain tasks depending on the needs of the user. This article will focus on NoSQL key-value cache databases.
What are the Top NoSQL Key Value Databases: Amazon DynamoDB, Oracle NoSQL Database, InfinityDB, Redis, Aerospike, Oracle Berkeley DB, Riak KV, Voldemort are some of the Top NoSQL Key Value Databases.
What are NoSQL Key Value Databases?
All those databases which are modeled in means other than the tabular relations used in relational databases are known as NO SQL databases. The data structure in key-value database differs from the RDBMS, and therefore some operations are faster in NoSQL and some in RDBMS. Key Value Store databases are classified as Key-Value Store eventually-consistent and Key Value Store ordered databases.
NoSQL key-value databases are the least complicated types of NoSQL databases. They store data as a key or attribute name with its value. Each data item has a pointer and a unique key. The key-value pairs are in the form of rows of associative arrays. Key-value databases use arbitrary strings to represent the key and the value could be a document or an image. Unlike, traditional relational databases, key-value stores do not have a specific schema.
Many key-value databases allow users to store persistent copies of data in flash drives, hard drives and other storage devices that can store data permanently. Other key-value databases only store data in memory and are generally known as key-value cache databases. NoSQL key-value cache databases allow users to retrieved data faster than databases that store data in disks. The cache allows users to quickly access data by reading and storing data in memory to facilitate easy retrieval when needed.
NoSQL databases are used in Bigdata to process large volume of information. NoSQL databases are also known as Not only SQL as may also support SQL like query languages. Any database that is modeled in means other than the tabular relations used in relational databases are called No SQL database.
NoSQL database can be classified as Key Value Cache, Key Value Store, Key Value Store Eventually Consistent, Key Value Store Ordered, Data Structures server, Tuple Store, Object Database, Document Store, and Wide Columnar Store.
What are NoSQL Key Value Databases
- Data Storage and Retrieval: The ability to store data is one of the primary functions of all databases. Key-value databases allow users to apply a key to each data item (value) and facilitate storage for immediate or future use.
- Caching: NoSQL key-value cache databases include integrated caching capabilities so they can keep frequently-used data in memory. This feature allows database users to quickly access data. In addition to caching objects, this feature allows application nodes to share frequently-used data.
- A Simple Data Structure: All key-value databases use a simple data structure and this is important because sometimes those extra features are not necessary. Database users can simply add new features when the need arises. The database’s simple associated arrays optimize its performance allowing users to quickly perform data-intensive operations.
- Scalability: NoSQL key-value databases are easy to scale without disrupting operations. Users can add and remove servers depending on their needs without causing undesirable disruptions.
Some of the benefits include:
- Rapid storage of data and information due to the simple data structure.
- High performance because the integrated caching feature allows users to store and retrieve data in the shortest time possible.
- Database users can make changes to the system in order to accommodate the changing needs of their organization with minimal disruptions to operations.
Top NoSQL Key Value Databases
Amazon DynamoDB
Amazon DynamoDB is a non-relational database that delivers reliable performance at any scale. It's a fully managed, multi-region, multi-master database that provides consistent single-digit millisecond latency, and offers built-in security, backup and restore, and in-memory caching. More than 100,000 AWS customers have chosen DynamoDB for mobile, web, gaming, ad tech, IoT, and many other applications that need low-latency data access. DynamoDB delivers consistent, single-digit millisecond responsiveness at any scale. Build apps with virtually unlimited throughput and storage. Add an in-memory cache that reduces response times from milliseconds to microseconds, without any app changes. DynamoDB is a serverless database that automatically…
• Time To Live (TTL): Set a specific time stamp to delete expired items from tables
• On-demand backup and restore allows users to create full backups of DynamoDB tables’ data for data archiving
• Automated system management
• Amazon DynamoDB Accelerator (DAX) delivers fast read performance for DynamoDB tables at scale
• The DynamoDB console and APIs allow users to create, update, delete, and query tables; adjust throughput
• VPC endpoints: Logical entities within a VPC that create a private connection between a VPC and DynamoDB without requiring access over the internet
Oracle NoSQL Database
Oracle NoSQL Database provides a reliable and flexible data management of configurable set of nodes. This particular scalable and NoSQL database can be highly trusted when it comes to businesses managing all their data to ensure effectivity.Using graph database uses nodes and edges to represent an entity that establishes relationship and connections. Oracle NoSQL Database, a sharded system, allocates data uniformly across other shards in the groups. Storage nodes are then replicated to establish high availability to maintain consistency.Oracle NoSQL Database is integrated with different Oracle and open source applications to work on development and operation of big data applications…
InfinityDB
InfinityDB uses a rugged internal storage update protocol for persistence on demand or cache spilling to disk for large amounts of data that maintains system-wide data integrity, and survives abrupt application termination, file system bugs, and kernel panics. The single data file remains up-to-date, safe, correct, and usable through any event. There is no log-based recovery, hence restart and recovery is immediate in all cases. InfinityDB is designed to use one single file. The combination of this feature and the instant recovery help make this product administrator free. No logs need to be archived or re-applied. There are no configuration…
• Nestable Multi-value (can represent trees, graphs, K/V, documents, huge sparse arrays, tables)
• Transactions: Optimistic ACID for threads, or global ACD for bulk operations
• Simple API: Instant developer productivity
• Dynamic views of data for queries: Set logic views, delta views, ranges
• Self administration (one file, no DBA, no upgrade scripts, no logs, no configuration)
• Runtime schema evolution (for forwards/backwards compatibility)
Redis
Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache and message broker. It supports data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs and geospatial indexes with radius queries. Redis has built-in replication, Lua scripting, LRU eviction, transactions and different levels of on-disk persistence, and provides high availability via Redis Sentinel and automatic partitioning with Redis Cluster. Run atomic operations on these types, like appending to a string; incrementing the value in a hash; pushing an element to a list; computing set intersection, union and difference; or getting the member with highest ranking in a sorted set.…
• Keyspace notifications allows clients to subscribe to Pub/Sub channels
• Sorted sets to create secondary indexes by ID or other numerical fields
• Geo API that allows users to query by radius, and latitude & longitude
• Redis Hashing: Stores data in the form of a key and a map
• Single-rooted replication tree
• Client APIs developed in all the popular languages such as C, Ruby, Java, javascript, and Python
• Open source
Aerospike
Aerospike is the world’s leading enterprise-grade, internet scale, key-value store database whose patented Hybrid Memory Architecture™ enables digital transformation by powering real-time, mission critical applications and analysis. Only Aerospike delivers strong consistency, predictable high performance and low TCO with linear scalability. Serving the financial services, banking, telecommunications, technology, retail / ecommerce, adtech / martech and gaming industries, Aerospike has proven customer deployments with zero downtime. The patented Aerospike Hybrid Memory Architecture™ achieves strong consistency simultaneously with high performance and thus can be used at the core of any data architecture. Aerospike powers SoRs where correctness is required at internet scale,…
• Patented Hybrid Memory Architecture delivers elastic, predictable performance at internet scale
• Real-time decisioning on large, continuously updated datasets
• Dynamic Network Optimization drives better quality of service and allows for optimal use of resources
• The sharding removes any need to overlook to make sure if balanced correctly
• Transport Layer Security
• Server side clustering
Oracle Berkeley DB
Oracle Berkeley DB is a family of embedded key-value database libraries providing scalable high-performance data management services to applications. Berkeley DB offers advanced features including transactional data storage, highly concurrent access, scalability on large SMP systems, replication for high availability, and fault tolerance in a self-contained, small footprint software library. The Berkeley DB uses simple function-call APIs for data access and management. Berkeley DB enables the development of custom data management solutions, without the overhead traditionally associated with such custom projects. Berkeley DB provides a collection of well-proven building-block technologies that can be configured to address any application need from…
• Pure in-memory data management for ultra-low latency and high performance
• Btree, Queue, Recno, Hash data indexes
• Recoverable ACID transactions with multiple isolation levels (including MVCC)
• Partition data based on key ranges
• Support for compression of data items
• Database services in a self-contained software library
Riak KV
Riak KV is a distributed NoSQL key-value database with advanced local and multi-cluster replication that guarantees reads and writes even in the event of hardware failures or network partitions. With a key/value design that delivers powerful – yet simple – data models for storing massive amounts of unstructured data, Riak KV is built to handle a variety of challenges facing Big Data applications that include tracking user or session information, storing connected device data and replicating data across the globe. Riak KV automates data distribution across the cluster to achieve fast performance and robust business continuity with a masterless architecture…
• Conflict-free replicated data types (CRDTs): flags, registers, counters, sets, and maps
• Active Cluster Configuration – Achieve data locality by serving clients at low latency from the nearest datacenter
• Availability Zones: Efficient multi-cluster replication and data redundancy within a geographic region
• Key/value NoSQL data model provides flexibility with no pre-defined schema
• Enhanced error logging and reporting
• Automatic data compression using the Snappy compression library
Voldemort
Voldemort is an open source distributed database based on Amazon Dynamo. Voldemort uses in-memory caching to eliminate a separate caching tier. It has a storage layer that is possible to emulate. Voldemort reads and writes scale horizontally. The API decides data replication and placement and accommodates a wide range of application-specific strategies. The Voldemort distributed data store supports pluggable placement strategies for distribution across data centers. Data is automatically replicated across servers. Data is partitioned meaning a single server contains only a portion of the total data. Each data node is independent to avoid central point of failure. Pluggable serialization…
• Pluggable Storage Engines -- BDB-JE, MySQL, Read-Only
• Data portioning is transparent, and allows for cluster expansion without rebalancing all data
• Topology aware routing
• Ready-made caching layer
• Pluggable serialization -- Protocol Buffers, Thrift, Avro and Java Serialization
• Included JMX instrumentation for increased visibility into the internal monitoring, validation
• Open source
Voldemort What are NoSQL Key Value Databases? NoSQL key-value databases are the least complicated types of NoSQL databases. They store data as a key or attribute name with its value. Each data item has a pointer and a unique key. The key-value pairs are in the form of rows of associative arrays. Key-value databases use arbitrary strings to represent the key and the value could be a document or an image. Unlike, traditional relational databases, key-value stores do not have a specific schema. What are the Top NoSQL Key Value Databases? Amazon DynamoDB, Oracle NoSQL Database, InfinityDB, Redis, Aerospike, Oracle Berkeley DB, Riak KV, Voldemort are some of the Top NoSQL Key Value Databases.
ADDITIONAL INFORMATION
Another KV list without mentioning Redis… I’d love to understand how the writer did research and still managed to avoid a reference to it 🙂