DBMS > Amazon DynamoDB vs. HBase vs. Hyprcubd vs. Memcached vs. Sphinx

System Properties Comparison Amazon DynamoDB vs. HBase vs. Hyprcubd vs. Memcached vs. Sphinx

Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

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

Wide-column store based on Apache Hadoop and on concepts of BigTable

Serverless Time Series DBMS

In-memory key-value store, originally intended for caching

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

Primary database model

Document store
Key-value 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	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	19.42
Rank	#32	Overall
	#4	Key-value stores

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

aws.amazon.com/dynamodb

hbase.apache.org

hyprcubd.com (offline)

www.memcached.org

sphinxsearch.com

Technical documentation

docs.aws.amazon.com/dynamodb

hbase.apache.org/book.html

github.com/memcached/memcached/wiki

sphinxsearch.com/docs

Developer

Amazon

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Hyprcubd, Inc.

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Sphinx Technologies Inc.

Initial release

2012

2008

2003

2001

Current release

2.3.4, January 2021

1.6.25, March 2024

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

commercial

Open Source

BSD license

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
Unix
Windows

using Cygwin

hosted

FreeBSD
Linux
OS X
Unix
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

schema-free

schema-free, schema definition possible

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

yes

time, int, uint, float, string

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-like query language

SQL-like query language (SphinxQL)

APIs and other access methods

RESTful HTTP API

Java API
RESTful HTTP API
Thrift

gRPC (https)

Proprietary protocol

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C#
C++
Groovy
Java
PHP
Python
Scala

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

Coprocessors in Java

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

none

Repcached, a Memcached patch, provides this functionallity

none

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency or Eventual Consistency

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

Single row ACID (across millions of columns)

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

User concepts

Access control

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

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

token access

yes

using SASL (Simple Authentication and Security Layer) protocol

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