Aerospike vs Neo4j

Overview

Neo4j

Stacks1.2K

Followers1.4K

Votes351

GitHub Stars15.3K

Forks2.5K

Aerospike

Stacks200

Followers288

Votes48

GitHub Stars1.3K

Forks196

Aerospike vs Neo4j: What are the differences?

Introduction

When comparing Aerospike and Neo4j, it is important to understand the key differences between the two databases.

Data Model: Aerospike is a key-value store that organizes data in bins within records, making it suitable for simple schema-less data. In contrast, Neo4j is a graph database that stores data in nodes, relationships, and properties, allowing for complex relationships and queries.
Query Language: Aerospike utilizes a proprietary query language called Aerospike Query Language (AQL) which supports complex search conditions. Neo4j, on the other hand, uses Cypher Query Language, a powerful graph query language designed for graph traversal and pattern matching.
Scalability: Aerospike provides automatic sharding and replication for scalability and high availability across multiple nodes. Neo4j has limitations in scaling horizontally due to its focus on graph traversal algorithms and data consistency.
Use Cases: Aerospike is suitable for real-time applications that require low-latency key-value access, such as advertising platforms and recommendation engines. Neo4j excels in applications that involve complex relationships and graph-based analysis, like social networks and fraud detection.
Consistency Model: Aerospike offers eventual consistency by default, where updates are propagated asynchronously. Neo4j provides strong consistency guarantees to ensure data integrity and transactional support in a distributed environment.
Community and Ecosystem: Neo4j has a larger and more active community, offering extensive documentation, tutorials, and support resources. In comparison, Aerospike has a smaller but dedicated community with a focus on performance and scalability.

In Summary, Aerospike and Neo4j differ in their data models, query languages, scalability, use cases, consistency models, and community support.

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Advice on Neo4j, Aerospike

Jaime

none at none

Aug 31, 2020

Needs advice

Hi, I want to create a social network for students, and I was wondering which of these three Oriented Graph DB's would you recommend. I plan to implement machine learning algorithms such as k-means and others to give recommendations and some basic data analyses; also, everything is going to be hosted in the cloud, so I expect the DB to be hosted there. I want the queries to be as fast as possible, and I like good tools to monitor my data. I would appreciate any recommendations or thoughts.

Context:

I released the MVP 6 months ago and got almost 600 users just from my university in Colombia, But now I want to expand it all over my country. I am expecting more or less 20000 users.

56.4k views56.4k

Comments

Detailed Comparison

Neo4j	Aerospike
Neo4j stores data in nodes connected by directed, typed relationships with properties on both, also known as a Property Graph. It is a high performance graph store with all the features expected of a mature and robust database, like a friendly query language and ACID transactions.	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.
intuitive, using a graph model for data representation;reliable, with full ACID transactions;durable and fast, using a custom disk-based, native storage engine;massively scalable, up to several billion nodes/relationships/properties;highly-available, when distributed across multiple machines;expressive, with a powerful, human readable graph query language;fast, with a powerful traversal framework for high-speed graph queries;embeddable, with a few small jars;simple, accessible by a convenient REST interface or an object-oriented Java API	99% of reads/writes complete in under 1 millisecond.;Predictable low latency at high throughput – second to none. Read the YCSB Benchmark.;The secret sauce? A thousand things done right. Server code in ‘C’ (not Java or Erlang) precisely tuned to avoid context switching and memory copies. Highly parallelized multi-threaded, multi-core, multi-cpu, multi-SSD execution.;Indexes are always stored in RAM. Pure RAM mode is backed by spinning disks. In hybrid mode, individual tables are stored in either RAM or flash.
Statistics
GitHub Stars 15.3K	GitHub Stars 1.3K
GitHub Forks 2.5K	GitHub Forks 196
Stacks 1.2K	Stacks 200
Followers 1.4K	Followers 288
Votes 351	Votes 48
Pros & Cons
Pros 69 Cypher – graph query language 61 Great graphdb 33 Open source 31 Rest api 27 High-Performance Native API Cons 9 Comparably slow 4 Can't store a vertex as JSON 1 Doesn't have a managed cloud service at low cost	Pros 16 Ram and/or ssd persistence 12 Easy clustering support 5 Easy setup 4 Acid 3 Petabyte Scale

What are some alternatives to Neo4j, Aerospike?

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.

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.

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

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

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 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.

Dgraph

Dgraph's goal is to provide Google production level scale and throughput, with low enough latency to be serving real time user queries, over terabytes of structured data. Dgraph supports GraphQL-like query syntax, and responds in JSON and Protocol Buffers over GRPC and HTTP.

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

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.

RedisGraph

RedisGraph is a graph database developed from scratch on top of Redis, using the new Redis Modules API to extend Redis with new commands and capabilities. Its main features include: - Simple, fast indexing and querying - Data stored in RAM, using memory-efficient custom data structures - On disk persistence - Tabular result sets - Simple and popular graph query language (Cypher) - Data Filtering, Aggregation and ordering

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Aerospike vs Neo4j: What are the differences?

Introduction

When comparing Aerospike and Neo4j, it is important to understand the key differences between the two databases.

Data Model: Aerospike is a key-value store that organizes data in bins within records, making it suitable for simple schema-less data. In contrast, Neo4j is a graph database that stores data in nodes, relationships, and properties, allowing for complex relationships and queries.
Query Language: Aerospike utilizes a proprietary query language called Aerospike Query Language (AQL) which supports complex search conditions. Neo4j, on the other hand, uses Cypher Query Language, a powerful graph query language designed for graph traversal and pattern matching.
Scalability: Aerospike provides automatic sharding and replication for scalability and high availability across multiple nodes. Neo4j has limitations in scaling horizontally due to its focus on graph traversal algorithms and data consistency.
Use Cases: Aerospike is suitable for real-time applications that require low-latency key-value access, such as advertising platforms and recommendation engines. Neo4j excels in applications that involve complex relationships and graph-based analysis, like social networks and fraud detection.
Consistency Model: Aerospike offers eventual consistency by default, where updates are propagated asynchronously. Neo4j provides strong consistency guarantees to ensure data integrity and transactional support in a distributed environment.
Community and Ecosystem: Neo4j has a larger and more active community, offering extensive documentation, tutorials, and support resources. In comparison, Aerospike has a smaller but dedicated community with a focus on performance and scalability.

In Summary, Aerospike and Neo4j differ in their data models, query languages, scalability, use cases, consistency models, and community support.