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  1. Stackups
  2. Application & Data
  3. In-Memory Databases
  4. In Memory Databases
  5. Hazelcast vs Heroku Postgres

Hazelcast vs Heroku Postgres

OverviewDecisionsComparisonAlternatives

Overview

Hazelcast
Hazelcast
Stacks427
Followers474
Votes59
GitHub Stars6.4K
Forks1.9K
Heroku Postgres
Heroku Postgres
Stacks607
Followers314
Votes38

Hazelcast vs Heroku Postgres: What are the differences?

Developers describe Hazelcast as "Clustering and highly scalable data distribution platform for Java". 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. On the other hand, Heroku Postgres is detailed as "Heroku's Database-as-a-Service. Based on the most powerful open-source database, PostgreSQL". Heroku Postgres provides a SQL database-as-a-service that lets you focus on building your application instead of messing around with database management.

Hazelcast can be classified as a tool in the "In-Memory Databases" category, while Heroku Postgres is grouped under "PostgreSQL as a Service".

Some of the features offered by Hazelcast are:

  • Distributed implementations of java.util.{Queue, Set, List, Map}
  • Distributed implementation of java.util.concurrent.locks.Lock
  • Distributed implementation of java.util.concurrent.ExecutorService

On the other hand, Heroku Postgres provides the following key features:

  • High Availability
  • Rollback
  • Dataclips

"High Availibility" is the top reason why over 4 developers like Hazelcast, while over 27 developers mention "Easy to setup" as the leading cause for choosing Heroku Postgres.

Hazelcast is an open source tool with 3.18K GitHub stars and 1.16K GitHub forks. Here's a link to Hazelcast's open source repository on GitHub.

According to the StackShare community, Heroku Postgres has a broader approval, being mentioned in 74 company stacks & 39 developers stacks; compared to Hazelcast, which is listed in 26 company stacks and 16 developer stacks.

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Advice on Hazelcast, Heroku Postgres

Jorge
Jorge

Jan 15, 2020

Needs advice

Considering moving part of our PostgreSQL database infrastructure to the cloud, however, not quite sure between AWS, Heroku, Azure and Google cloud. Things to consider: The main reason is for backing up and centralize all our data in the cloud. With that in mind the main elements are: -Pricing for storage. -Small team. -No need for high throughput. -Support for docker swarm and Kubernetes.

51.8k views51.8k
Comments

Detailed Comparison

Hazelcast
Hazelcast
Heroku Postgres
Heroku Postgres

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.

Heroku Postgres provides a SQL database-as-a-service that lets you focus on building your application instead of messing around with database management.

Distributed implementations of java.util.{Queue, Set, List, Map};Distributed implementation of java.util.concurrent.locks.Lock;Distributed implementation of java.util.concurrent.ExecutorService;Distributed MultiMap for one-to-many relationships;Distributed Topic for publish/subscribe messaging;Synchronous (write-through) and asynchronous (write-behind) persistence;Transaction support;Socket level encryption support for secure clusters;Second level cache provider for Hibernate;Monitoring and management of the cluster via JMX;Dynamic HTTP session clustering;Support for cluster info and membership events;Dynamic discovery, scaling, partitioning with backups and fail-over
High Availability;Rollback;Dataclips;Automated Health Checks
Statistics
GitHub Stars
6.4K
GitHub Stars
-
GitHub Forks
1.9K
GitHub Forks
-
Stacks
427
Stacks
607
Followers
474
Followers
314
Votes
59
Votes
38
Pros & Cons
Pros
  • 11
    High Availibility
  • 6
    Distributed Locking
  • 6
    Distributed compute
  • 5
    Sharding
  • 4
    Load balancing
Cons
  • 4
    License needed for SSL
Pros
  • 29
    Easy to setup
  • 3
    Dataclips for sharing queries
  • 3
    Extremely reliable
  • 3
    Follower databases
Cons
  • 2
    Super expensive
Integrations
Java
Java
Spring
Spring
PostgreSQL
PostgreSQL
Heroku
Heroku

What are some alternatives to Hazelcast, Heroku Postgres?

Redis

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.

Aerospike

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.

MemSQL

MemSQL

MemSQL converges transactions and analytics for sub-second data processing and reporting. Real-time businesses can build robust applications on a simple and scalable infrastructure that complements and extends existing data pipelines.

Apache Ignite

Apache Ignite

It is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads delivering in-memory speeds at petabyte scale

Amazon RDS for PostgreSQL

Amazon RDS for PostgreSQL

Amazon RDS manages complex and time-consuming administrative tasks such as PostgreSQL software installation and upgrades, storage management, replication for high availability and back-ups for disaster recovery. With just a few clicks in the AWS Management Console, you can deploy a PostgreSQL database with automatically configured database parameters for optimal performance. Amazon RDS for PostgreSQL database instances can be provisioned with either standard storage or Provisioned IOPS storage. Once provisioned, you can scale from 10GB to 3TB of storage and from 1,000 IOPS to 30,000 IOPS.

SAP HANA

SAP HANA

It is an application that uses in-memory database technology that allows the processing of massive amounts of real-time data in a short time. The in-memory computing engine allows it to process data stored in RAM as opposed to reading it from a disk.

VoltDB

VoltDB

VoltDB is a fundamental redesign of the RDBMS that provides unparalleled performance and scalability on bare-metal, virtualized and cloud infrastructures. VoltDB is a modern in-memory architecture that supports both SQL + Java with data durability and fault tolerance.

ElephantSQL

ElephantSQL

ElephantSQL hosts PostgreSQL on Amazon EC2 in multiple regions and availability zones. The servers are continuously transferring the Write-Ahead-Log (the transaction log) to S3 for maximum reliability.

Tarantool

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

Azure Redis Cache

Azure Redis Cache

It perfectly complements Azure database services such as Cosmos DB. It provides a cost-effective solution to scale read and write throughput of your data tier. Store and share database query results, session states, static contents, and more using a common cache-aside pattern.

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