DBMS > Amazon Neptune vs. Badger vs. Geode vs. HEAVY.AI vs. Microsoft SQL Server

System Properties Comparison Amazon Neptune vs. Badger vs. Geode vs. HEAVY.AI vs. Microsoft SQL Server

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

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

Microsofts flagship relational DBMS

Primary database model

Graph DBMS
RDF store

Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	2.20
Rank	#119	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

aws.amazon.com/neptune

github.com/dgraph-io/badger

geode.apache.org

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

www.microsoft.com/en-us/sql-server

Technical documentation

aws.amazon.com/neptune/developer-resources

godoc.org/github.com/dgraph-io/badger

geode.apache.org/docs

docs.heavy.ai

learn.microsoft.com/en-US/sql/sql-server

Developer

Amazon

DGraph Labs

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

HEAVY.AI, Inc.

Microsoft

Initial release

2017

2002

2016

1989

Current release

1.1, February 2017

5.10, January 2022

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

Apache Version 2; enterprise edition available

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C++ and CUDA

C++

Server operating systems

hosted

BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

the JDK (8 or later) is also required

Linux

Linux
Windows

Data scheme

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language (OQL)

yes

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

Java Client API
Memcached protocol
RESTful HTTP API

JDBC
ODBC
Thrift
Vega

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

.Net
All JVM based languages
C++
Groovy
Java
Scala

All languages supporting JDBC/ODBC/Thrift
Python

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Server-side scripts

Stored procedures

user defined functions

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

tables can be distributed across several files (horizontal partitioning); sharding through federation

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

none

Multi-source replication

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

yes, on a single node

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

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)

Access rights per client and object definable

fine grained access rights according to SQL-standard

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