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Aerospike vs RocksDB: What are the differences?
### Introduction
Key differences between Aerospike and RocksDB are outlined below:
### 1. Data Model:
Aerospike is a distributed, NoSQL database that stores data in a key-value format, allowing for easy retrieval and manipulation of data. In contrast, RocksDB is a key-value store that is optimized for flash and RAM storage, providing high performance and low latency for read-heavy workloads.
### 2. Storage Engine:
Aerospike uses an in-memory storage engine to achieve fast read and write operations, while also persisting data to disk for durability. RocksDB, on the other hand, is a persistent storage engine that writes data to disk in an efficient manner, making it suitable for applications that require high write throughput.
### 3. Consistency Model:
Aerospike provides strong consistency guarantees, ensuring that data is always up-to-date and accurate across all nodes in a cluster. RocksDB, on the other hand, offers eventual consistency, which allows for faster write operations at the expense of potential data inconsistencies that may need to be reconciled later.
### 4. Partitioning:
Aerospike automatically partitions data across nodes in a cluster, enabling horizontal scalability and fault tolerance. RocksDB does not offer built-in partitioning capabilities, requiring developers to handle data distribution and replication manually, which can be more complex and error-prone.
### 5. Language Support:
Aerospike provides robust client libraries for a variety of programming languages, making it easy to integrate with existing applications. RocksDB, on the other hand, primarily supports C++, with limited bindings available for other languages, potentially limiting its usage in certain development environments.
### 6. Use Cases:
Aerospike is well-suited for real-time, high-performance applications that require low latency and high availability, such as ad tech platforms and financial services. RocksDB, on the other hand, is better suited for embedded systems, caching layers, and applications that prioritize efficient disk utilization and write speed over network performance.
In Summary, Aerospike and RocksDB differ in their data models, storage engines, consistency models, partitioning strategies, language support, and use cases.
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Learn MorePros of Aerospike
Pros of RocksDB
Pros of Aerospike
- Ram and/or ssd persistence16
- Easy clustering support12
- Easy setup5
- Acid4
- Petabyte Scale3
- Scale3
- Performance better than Redis3
- Ease of use2
Pros of RocksDB
- Very fast5
- Made by Facebook3
- Consistent performance2
- Ability to add logic to the database layer where needed1
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What is Aerospike?
Aerospike is an open-source, modern database built from the ground up to push the limits of flash storage, processors and networks. It was designed to operate with predictable low latency at high throughput with uncompromising reliability – both high availability and ACID guarantees.
What is RocksDB?
RocksDB is an embeddable persistent key-value store for fast storage. RocksDB can also be the foundation for a client-server database but our current focus is on embedded workloads. RocksDB builds on LevelDB to be scalable to run on servers with many CPU cores, to efficiently use fast storage, to support IO-bound, in-memory and write-once workloads, and to be flexible to allow for innovation.
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What companies use Aerospike?
What companies use RocksDB?
What companies use Aerospike?
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What are some alternatives to Aerospike and RocksDB?
Redis
Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.
Riak
Riak is a distributed database designed to deliver maximum data availability by distributing data across multiple servers. As long as your client can reach one Riak server, it should be able to write data. In most failure scenarios, the data you want to read should be available, although it may not be the most up-to-date version of that data.
Cassandra
Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.
Elasticsearch
Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).
Tarantool
It is designed to give you the flexibility, scalability, and performance that you want, as well as the reliability and manageability that you need in mission-critical applications