DBMS > Amazon Redshift vs. dBASE vs. Elasticsearch vs. GreptimeDB

System Properties Comparison Amazon Redshift vs. dBASE vs. Elasticsearch vs. GreptimeDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

dBase was one of the first databases with a development environment on PC's. Its latest version dBase V is still sold as dBase classic, which needs a DOS Emulation. The up-to-date product is dBase plus.

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

An open source Time Series DBMS built for increased scalability, high performance and efficiency

Primary database model

Relational DBMS

Search engine

Time Series DBMS

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	9.70
Rank	#44	Overall
	#28	Relational DBMS

Score	132.83
Rank	#7	Overall
	#1	Search engines

Score	0.12
Rank	#351	Overall
	#34	Time Series DBMS

Website

aws.amazon.com/redshift

www.dbase.com

www.elastic.co/elasticsearch

greptime.com

Technical documentation

docs.aws.amazon.com/redshift

www.dbase.com/support/knowledgebase

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

docs.greptime.com

Developer

Amazon (based on PostgreSQL)

Asthon Tate

Elastic

Greptime Inc.

Initial release

2012

1979

2010

2022

Current release

dBASE 2019, 2019

8.6, January 2023

License

Commercial or Open Source

commercial

Open Source

Elastic License

Open Source

Apache Version 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

Rust

Server operating systems

hosted

DOS

dBase Classic
Windows

dBase Pro

All OS with a Java VM

Android
Docker
FreeBSD
Linux
macOS
Windows

Data scheme

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

schema-free, schema definition possible

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

restricted

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC

none

The IDE can access other DBMS or ODBC-sources.

Java API
RESTful HTTP/JSON API

gRPC
HTTP API
JDBC

Supported programming languages

All languages supporting JDBC/ODBC

dBase proprietary IDE

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

C++
Erlang
Go
Java
JavaScript

Server-side scripts

Stored procedures

user defined functions

in Python

The IDE can access stored procedures in other database systems.

yes

Python

Triggers

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

not for dBase internal data, but IDE does support transactions when accessing external DBMS

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

Memcached and Redis integration

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

Simple rights management via user accounts

More information provided by the system vendor

Specific characteristics

GreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more

Competitive advantages

- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more

Typical application scenarios

For IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more

Key customers

Greptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more

Market metrics

GreptimeDB has garnered global recognition by topping GitHub trends following its...
» more

Licensing and pricing models

GreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.