DBMS > Amazon DynamoDB vs. HyperSQL vs. InfluxDB vs. LevelDB vs. Linter

System Properties Comparison Amazon DynamoDB vs. HyperSQL vs. InfluxDB vs. LevelDB vs. Linter

Editorial information provided by DB-Engines

Name

Description

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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

DBMS for storing time series, events and metrics

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

RDBMS for high security requirements

Primary database model

Document store
Key-value store

Secondary database models

Spatial DBMS

with GEO package

Spatial DBMS

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

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	24.39
Rank	#28	Overall
	#1	Time Series DBMS

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	0.12
Rank	#350	Overall
	#152	Relational DBMS

Website

aws.amazon.com/dynamodb

hsqldb.org

www.influxdata.com/products/influxdb-overview

github.com/google/leveldb

linter.ru

Technical documentation

docs.aws.amazon.com/dynamodb

hsqldb.org/web/hsqlDocsFrame.html

docs.influxdata.com/influxdb

github.com/google/leveldb/blob/main/doc/index.md

Developer

Amazon

Google

relex.ru

Initial release

2012

2001

2013

2011

1990

Current release

2.7.2, June 2023

2.7.6, April 2024

1.23, February 2021

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

based on BSD license

Open Source

MIT-License; commercial enterprise version available

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

C++

C and C++

Server operating systems

hosted

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux
OS X

through Homebrew

Illumos
Linux
OS X
Windows

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

RESTful HTTP API

HTTP API

JDBC via HTTP
JDBC
ODBC

HTTP API
JSON over UDP

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

All languages supporting JDBC/ODBC
Java

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

Server-side scripts

Stored procedures

Java, SQL

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

in enterprise version only

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

selectable replication factor

in enterprise version only

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

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

yes

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

In-memory capabilities

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

yes

Depending on used storage engine

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

simple rights management via user accounts

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Key customers

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Market metrics

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Licensing and pricing models

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