DBMS > Amazon Redshift vs. etcd vs. HyperSQL vs. Solr vs. TinkerGraph

System Properties Comparison Amazon Redshift vs. etcd vs. HyperSQL vs. Solr vs. TinkerGraph

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

A distributed reliable key-value store

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

A widely used distributed, scalable search engine based on Apache Lucene

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Secondary database models

Spatial DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	7.03
Rank	#54	Overall
	#5	Key-value stores

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	41.02
Rank	#24	Overall
	#3	Search engines

Score	0.13
Rank	#345	Overall
	#35	Graph DBMS

Website

aws.amazon.com/redshift

etcd.io
github.com/etcd-io/etcd

hsqldb.org

solr.apache.org

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

docs.aws.amazon.com/redshift

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

hsqldb.org/web/hsqlDocsFrame.html

solr.apache.org/resources.html

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Initial release

2012

2001

2006

2009

Current release

3.4, August 2019

2.7.2, June 2023

9.6.1, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

based on BSD license

Open Source

Apache Version 2

Open Source

Apache 2.0

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

Server operating systems

hosted

FreeBSD
Linux
Windows

experimental

All OS with a Java VM

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

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

yes

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

schema-free

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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.

yes

Secondary indexes

restricted

yes

All search fields are automatically indexed

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

Solr Parallel SQL Interface

APIs and other access methods

JDBC
ODBC

gRPC
JSON over HTTP

HTTP API

JDBC via HTTP
JDBC
ODBC

Java API
RESTful HTTP/JSON API

TinkerPop 3

Supported programming languages

All languages supporting JDBC/ODBC

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

All languages supporting JDBC/ODBC
Java

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Groovy
Java

Server-side scripts

Stored procedures

user defined functions

in Python

Java, SQL

Java plugins

Triggers

yes, watching key changes

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

none

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Relationships in graphs

Transaction concepts

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

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

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