DBMS > Amazon Neptune vs. H2 vs. Sphinx vs. XTDB

System Properties Comparison Amazon Neptune vs. H2 vs. Sphinx vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Open source search engine for searching in data from different sources, e.g. relational databases

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Secondary database models

Spatial DBMS

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

Score	2.20
Rank	#113	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	7.57
Rank	#47	Overall
	#30	Relational DBMS

Score	5.97
Rank	#56	Overall
	#5	Search engines

Score	0.13
Rank	#330	Overall
	#45	Document stores

Website

aws.amazon.com/neptune

www.h2database.com

sphinxsearch.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

aws.amazon.com/neptune/developer-resources

www.h2database.com/html/main.html

sphinxsearch.com/docs

www.xtdb.com/docs

Developer

Amazon

Thomas Mueller

Sphinx Technologies Inc.

Juxt Ltd.

Initial release

2017

2005

2001

2019

Current release

2.2.220, July 2023

3.5.1, February 2023

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

GPL version 2, commercial licence available

Open Source

MIT License

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

C++

Clojure

Server operating systems

hosted

All OS with a Java VM

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

full-text index on all search fields

yes

SQL

Support of SQL

yes

SQL-like query language (SphinxQL)

limited SQL, making use of Apache Calcite

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

JDBC
ODBC

Proprietary protocol

HTTP REST
JDBC

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

Java

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Clojure
Java

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

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.

With clustering: 2 database servers on different computers operate on identical copies of a database

none

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

yes

The original contents of fields are not stored in the Sphinx index.

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

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More resources

DB-Engines blog posts

The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

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