DBMS > BigObject vs. Elasticsearch vs. Galaxybase

System Properties Comparison BigObject vs. Elasticsearch vs. Galaxybase

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

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

Scalable, ACID-compliant native distributed parallel graph platform

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Search engine
Vector DBMS

Graph DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.14
Rank	#333	Overall
	#145	Relational DBMS

Score	123.81
Rank	#9	Overall
	#1	Search engines
	#1	Vector DBMS

Score	0.00
Rank	#385	Overall
	#41	Graph DBMS

Website

bigobject.io

www.elastic.co/elasticsearch

galaxybase.com

Technical documentation

docs.bigobject.io

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

Developer

BigObject, Inc.

Elastic

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

Initial release

2015

2010

2017

Current release

8.6, January 2023

Nov 20, November 2021

License

Commercial or Open Source

commercial

free community edition available

Open Source

Elastic License

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C and Java

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

All OS with a Java VM

Linux

Data scheme

yes

schema-free

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

Strong typed schema

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

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

Java API
RESTful HTTP/JSON API

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

Supported programming languages

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

Go
Java
Python

Server-side scripts

Stored procedures

Lua

yes

user defined procedures and functions

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

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

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

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

yes

User concepts

Access control

Role-based access control

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More resources

DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2017
2 January 2018, Paul Andlinger, Matthias Gelbmann

Elasticsearch moved into the top 10 most popular database management systems
3 July 2017, Matthias Gelbmann

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

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Recent citations in the news

OpenSearch 3.0 hits: First major release under Linux Foundation as it battles ElasticSearch for mindshare
7 May 2025, devclass

OpenSearch 3.0 targets fast AI search with MCP and GPU-powered vectors
7 May 2025, Blocks and Files

OpenSearch in 2025: Much more than an Elasticsearch fork
28 April 2025, InfoWorld

Amazon OpenSearch Service announces Standard and Extended Support dates for Elasticsearch and OpenSearch versions
7 November 2024, Amazon Web Services

Elasticsearch Now Available as a Native Grounding Engine on Google Cloud’s Vertex AI Platform
9 April 2025, Business Wire

provided by Google News

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