DBMS > Amazon SimpleDB vs. HEAVY.AI vs. Neo4j vs. RocksDB vs. Splice Machine

System Properties Comparison Amazon SimpleDB vs. HEAVY.AI vs. Neo4j vs. RocksDB vs. Splice Machine

Editorial information provided by DB-Engines

Name

Description

Hosted simple database service by Amazon, with the data stored in the Amazon Cloud.

There is an unrelated product called SimpleDB developed by Edward Sciore

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Secondary database models

Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	1.88
Rank	#133	Overall
	#23	Key-value stores

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	44.89
Rank	#21	Overall
	#1	Graph DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Website

aws.amazon.com/simpledb

github.com/heavyai/heavydb
www.heavy.ai

neo4j.com

rocksdb.org

splicemachine.com

Technical documentation

docs.aws.amazon.com/simpledb

docs.heavy.ai

neo4j.com/docs

github.com/facebook/rocksdb/wiki

splicemachine.com/how-it-works

Developer

Amazon

HEAVY.AI, Inc.

Neo4j, Inc.

Facebook, Inc.

Splice Machine

Initial release

2007

2016

2007

2013

2014

Current release

5.10, January 2022

5.20, May 2024

9.2.1, May 2024

3.1, March 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; enterprise edition available

Open Source

GPL version3, commercial licenses available

Open Source

BSD

Open Source

AGPL 3.0, commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.

Implementation language

C++ and CUDA

Java, Scala

C++

Java

Server operating systems

hosted

Linux

Can also be used server-less as embedded Java database.
OS X
Solaris
Windows

Linux

Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-free and schema-optional

schema-free

yes

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

All columns are indexed automatically

yes

pluggable indexing subsystem, by default Apache Lucene

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
Thrift
Vega

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

C++ API
Java API

JDBC
Native Spark Datasource
ODBC

Supported programming languages

.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala

All languages supporting JDBC/ODBC/Thrift
Python

.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala

C
C++
Go
Java
Perl
Python
Ruby

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

yes

User defined Procedures and Functions

yes

Java

Triggers

yes

via event handler

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

Sharding

Round robin

yes using Neo4j Fabric

horizontal partitioning

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

Causal Clustering using Raft protocol

available in in Enterprise Version only

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Causal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Concurrent data updates can be detected by the application

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)

Access rights for users, groups and roles according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
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Market metrics

Neo4j boasts the world's largest graph database ecosystem with more than 140 million...
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Licensing and pricing models

GPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
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