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

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

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Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

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

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	0.30
Rank	#258	Overall
	#20	Time Series DBMS

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

Score	151.25
Rank	#8	Overall
	#1	Search engines

Score	3.81
Rank	#85	Overall
	#7	Wide column stores

Website

axibase.com/products/axibase-time-series-database

github.com/dgraph-io/badger

www.elastic.co/elasticsearch

cloud.google.com/bigtable

Technical documentation

github.com/axibase/atsd

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

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

cloud.google.com/bigtable/docs

Developer

Axibase Corporation

DGraph Labs

Elastic

Google

Initial release

2013

2017

2010

2015

Current release

15585

7.8.0, June 2020

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

Open Source

Apache 2.0

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

Linux

BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

hosted

Data scheme

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

short, integer, long, float, double, decimal, string

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

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

Java API
RESTful HTTP/JSON API

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

Supported programming languages

Go
Java
PHP
Python
R
Ruby

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

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

Server-side scripts

Stored procedures

yes

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

Source-replica replication

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

yes

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

Transaction concepts

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

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, 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

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