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Aerospike vs Hazelcast: What are the differences?
Introduction:
Aerospike and Hazelcast are both distributed database systems that offer unique features and functionalities for various use cases. Here are the key differences between Aerospike and Hazelcast:
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Data Model and Querying Language:
- Aerospike: Aerospike uses a key-value data model, where each record is uniquely identified by a primary key. It supports querying using the Aerospike Query Language (ASQL) or a subset of SQL-like syntax for filtering and manipulating data.
- Hazelcast: Hazelcast uses a distributed computing platform that provides an in-memory key-value store, but it also supports other data structures like distributed maps, queues, topics, and more. It does not provide a dedicated querying language, but supports querying using MapReduce operations or Predicate-based filtering.
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Consistency and Replication:
- Aerospike: Aerospike ensures strong consistency guarantees through its reliable, distributed replication mechanism. It supports various replication configurations, including synchronous replication with automatic failover and eventual consistency configurations.
- Hazelcast: Hazelcast provides eventual consistency and best-effort replication with customizable trade-offs between consistency, availability, and partition tolerance. It allows users to define the desired consistency guarantee based on their application requirements.
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Scalability and Performance:
- Aerospike: Aerospike is built for high-performance and scalability. It provides automatic data partitioning and distribution across nodes in a cluster, enabling linear scalability and efficient utilization of resources. It also includes various mechanisms for data compression and optimization to enhance overall performance.
- Hazelcast: Hazelcast is designed to be highly scalable and can handle large datasets and high throughput workloads. It supports horizontal scaling by adding more nodes to the cluster, and provides partition-based data distribution to ensure optimal performance. Additionally, it offers various optimizations like data storage management and indexing for efficient data access.
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Supported Programming Languages:
- Aerospike: Aerospike provides client libraries and SDKs for multiple programming languages, including Java, C#, C, Node.js, Python, and more, making it accessible to developers from different technology stacks.
- Hazelcast: Hazelcast supports a wide range of programming languages, such as Java, .NET/C#, C++, Python, Node.js, and more, allowing developers to use their preferred language to interact with the database system.
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Data Durability and Persistence:
- Aerospike: Aerospike provides configurable data durability with the ability to persist data to disk and maintain replicas for fault tolerance. It offers various options for data backup and recovery, ensuring data integrity and availability even in the face of failures.
- Hazelcast: Hazelcast supports data persistence to disk, facilitating durability in case of server restarts or failures. However, it does not provide built-in replication and fault-tolerance mechanisms, so users need to configure external systems for replication and backup.
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Clustering and High Availability:
- Aerospike: Aerospike utilizes a distributed cluster architecture with built-in fault tolerance and automatic failover. It supports various clustering options like multi-site replication and rack-awareness, ensuring high availability and data accessibility.
- Hazelcast: Hazelcast relies on a distributed cluster setup to provide high availability and fault tolerance. It supports automatic data replication and recovery in case of node failures, ensuring continuous availability of data and services.
In Summary, Aerospike and Hazelcast differ in terms of data model, querying language, consistency guarantees, scalability, supported programming languages, data durability, and clustering/high availability.
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Learn MorePros of Aerospike
Pros of Hazelcast
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 Hazelcast
- High Availibility11
- Distributed Locking6
- Distributed compute6
- Sharding5
- Load balancing4
- Map-reduce functionality3
- Simple-to-use3
- Written in java. runs on jvm3
- Publish-subscribe3
- Sql query support in cluster wide3
- Optimis locking for map2
- Performance2
- Multiple client language support2
- Rest interface2
- Admin Interface (Management Center)1
- Better Documentation1
- Easy to use1
- Super Fast1
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Cons of Aerospike
Cons of Hazelcast
Cons of Aerospike
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Cons of Hazelcast
- License needed for SSL4
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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 Hazelcast?
With its various distributed data structures, distributed caching capabilities, elastic nature, memcache support, integration with Spring and Hibernate and more importantly with so many happy users, Hazelcast is feature-rich, enterprise-ready and developer-friendly in-memory data grid solution.
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What companies use Aerospike?
What companies use Hazelcast?
What companies use Aerospike?
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What tools integrate with Aerospike?
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What are some alternatives to Aerospike and Hazelcast?
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