DBMS > Badger vs. dBASE vs. Elasticsearch vs. Google Cloud Bigtable

System Properties Comparison Badger vs. dBASE vs. Elasticsearch vs. Google Cloud Bigtable

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Primary database model

Secondary database models

Document store

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

Score	0.10
Rank	#296	Overall
	#46	Key-value stores

Score	14.23
Rank	#39	Overall
	#24	Relational DBMS

Score	151.25
Rank	#8	Overall
	#1	Search engines

Score	3.81
Rank	#85	Overall
	#7	Wide column stores

Website

github.com/dgraph-io/badger

www.dbase.com

www.elastic.co/elasticsearch

cloud.google.com/bigtable

Technical documentation

godoc.org/github.com/dgraph-io/badger

www.dbase.com/support/knowledgebase

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

cloud.google.com/bigtable/docs

Developer

DGraph Labs

Asthon Tate

Elastic

Google

Initial release

2017

1979

2010

2015

Current release

dBASE 2019, 2019

7.8.0, June 2020

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2; Elastic License

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.

Elasticsearch Service on Elastic Cloud: Try out the official hosted Elasticsearch and Kibana offering available on Amazon Web Services, Google Cloud and Microsoft Azure that's powered by the creators of Elasticsearch.

Implementation language

Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

DOS

dBase Classic
Windows

dBase Pro

All OS with a Java VM

hosted

Data scheme

schema-free

yes

schema-free

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

schema-free

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

All search fields are automatically indexed

SQL

Support of SQL

SQL-like query language

APIs and other access methods

none

The IDE can access other DBMS or ODBC-sources.

Java API
RESTful HTTP/JSON API

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

Supported programming languages

dBase proprietary IDE

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

C#
C++
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

The IDE can access stored procedures in other database systems.

yes

Triggers

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Internal replication in Colossus, and regional replication between two clusters in different zones

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

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

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

Atomic single-row operations

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.

Memcached and Redis integration

User concepts

Access control

Access rights for users and roles

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

More information provided by the system vendor

Specific characteristics

Elasticsearch is an open source search and analytics engine. As the heart of the...
» more

Competitive advantages

Open source Real-time indexsearch, and analysis Horizontally scalable Distributed...
» more

Typical application scenarios

Enterprise search (search experiences for your workplace, apps, and websites), observability...
» more

Key customers

Thousands of organizations worldwide, including Cisco, eBay, Goldman Sachs, Microsoft,...
» more

Market metrics

Public as of October 2018 Distributed workforce with 1900+ employees around the globe...
» more

Licensing and pricing models

The Elastic Stack (Elasticsearch, Kibana, Beats, and Logstash) is free and open source...
» 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.