DBMS > Amazon Neptune vs. Datomic vs. NSDb vs. RocksDB vs. UniData,UniVerse

System Properties Comparison Amazon Neptune vs. Datomic vs. NSDb vs. RocksDB vs. UniData,UniVerse

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

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

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

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

Score	2.29
Rank	#113	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

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

Score	2.85
Rank	#98	Overall
	#1	Multivalue DBMS

Website

aws.amazon.com/neptune

www.datomic.com

nsdb.io

rocksdb.org

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

aws.amazon.com/neptune/developer-resources

docs.datomic.com

nsdb.io/Architecture

github.com/facebook/rocksdb/wiki

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Amazon

Cognitect

Facebook, Inc.

Rocket Software

Initial release

2017

2012

2017

2013

1985

Current release

1.0.7075, December 2023

9.2.1, May 2024

License

Commercial or Open Source

commercial

limited edition free

Open Source

Apache Version 2.0

Open Source

BSD

commercial

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.

Implementation language

Java, Clojure

Java, Scala

C++

Server operating systems

hosted

All OS with a Java VM

Linux
macOS

Linux

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

optional

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 fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

RESTful HTTP API

gRPC
HTTP REST
WebSocket

C++ API
Java API

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

Clojure
Java

Java
Scala

C
C++
Go
Java
Perl
Python
Ruby

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

Triggers

By using transaction functions

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

horizontal partitioning

none

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

But extensive use of caching in the application peers

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

yes

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

Using Apache Lucene

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

User concepts

Access control

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

Access rights according to SQL-standard and operating system based

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