DBMS > Amazon DynamoDB vs. Apache Drill vs. Apache Impala vs. Sphinx

System Properties Comparison Amazon DynamoDB vs. Apache Drill vs. Apache Impala vs. Sphinx

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Editorial information provided by DB-Engines

Name

Description

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

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

Analytic DBMS for Hadoop

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

Primary database model

Document store
Key-value store

Document store
Relational DBMS

Relational DBMS

Search engine

Secondary database models

Document store

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

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

aws.amazon.com/dynamodb

drill.apache.org

impala.apache.org

sphinxsearch.com

Technical documentation

docs.aws.amazon.com/dynamodb

drill.apache.org/docs

impala.apache.org/impala-docs.html

sphinxsearch.com/docs

Developer

Amazon

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Sphinx Technologies Inc.

Initial release

2012

2013

2001

Current release

1.20.3, January 2023

4.1.0, June 2022

3.5.1, February 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2

Open Source

Apache Version 2

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

C++

Server operating systems

hosted

Linux
OS X
Windows

Linux

FreeBSD
Linux
NetBSD
OS X
Solaris
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.

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

SQL-like DML and DDL statements

SQL-like query language (SphinxQL)

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

Proprietary protocol

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C++

All languages supporting JDBC/ODBC

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions and integration of map-reduce

Triggers

yes

by integration with AWS Lambda

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

none

Eventual 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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Depending on the underlying data source

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.

Depending on the underlying data source

User concepts

Access control

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

Depending on the underlying data source

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

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