DBMS > Amazon DynamoDB vs. Apache Druid vs. BaseX vs. Quasardb vs. Sphinx

System Properties Comparison Amazon DynamoDB vs. Apache Druid vs. BaseX vs. Quasardb vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

Distributed, high-performance timeseries database

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

Primary database model

Document store
Key-value store

Relational DBMS
Time Series DBMS

Native XML DBMS

Time Series DBMS

Search engine

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

Score	70.06
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	2.85
Rank	#96	Overall
	#50	Relational DBMS
	#6	Time Series DBMS

Score	1.56
Rank	#141	Overall
	#4	Native XML DBMS

Score	0.13
Rank	#332	Overall
	#28	Time Series DBMS

Score	5.97
Rank	#56	Overall
	#5	Search engines

Website

aws.amazon.com/dynamodb

Technical documentation

docs.aws.amazon.com/dynamodb

druid.apache.org/docs/latest/design

docs.basex.org

doc.quasar.ai/master

sphinxsearch.com/docs

Developer

Amazon

Apache Software Foundation and contributors

BaseX GmbH

quasardb

Sphinx Technologies Inc.

Initial release

2012

2007

2009

2001

Current release

30.0.0, June 2024

11.2, August 2024

3.14.1, January 2024

3.5.1, February 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache license v2

Open Source

BSD license

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

GPL version 2, commercial licence 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.

Implementation language

Java

C++

Server operating systems

hosted

Linux
OS X
Unix

Linux
OS X
Windows

BSD
Linux
OS X
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-less columns are supported

schema-free

yes

Typing

predefined data types such as float or date

yes

XQuery supports types

yes

integer and binary

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

with tags

yes

full-text index on all search fields

SQL

Support of SQL

SQL for querying

SQL-like query language

SQL-like query language (SphinxQL)

APIs and other access methods

RESTful HTTP API

JDBC
RESTful HTTP/JSON API

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

HTTP API

Proprietary protocol

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

Triggers

yes

by integration with AWS Lambda

yes

via events

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

Sharding

consistent hashing

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, via HDFS, S3 or other storage engines

none

Source-replica replication with selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

multiple readers, single writer

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

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

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Users with fine-grained authorization concept on 4 levels

Cryptographically strong user authentication and audit trail

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