DBMS > BigchainDB vs. Google Cloud Datastore vs. Hazelcast vs. OpenSearch vs. Trafodion

System Properties Comparison BigchainDB vs. Google Cloud Datastore vs. Hazelcast vs. OpenSearch vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

A widely adopted in-memory data grid

A distributed, RESTful search and analytics engine forked from Elasticsearch and based on Apache Lucene

Transactional SQL-on-Hadoop DBMS

Primary database model

Secondary database models

Document store

JSON support with IMDG 3.12

Vector DBMS

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

Score	0.85
Rank	#208	Overall
	#35	Document stores

Score	4.36
Rank	#72	Overall
	#12	Document stores

Score	5.46
Rank	#61	Overall
	#7	Key-value stores

Score	16.03
Rank	#37	Overall
	#4	Search engines

Website

www.bigchaindb.com

cloud.google.com/datastore

hazelcast.com

github.com/opensearch-project
opensearch.org

trafodion.apache.org

Technical documentation

bigchaindb.readthedocs.io/en/latest

cloud.google.com/datastore/docs

hazelcast.org/imdg/docs

opensearch.org/docs/latest

trafodion.apache.org/documentation.html

Developer

Google

Hazelcast

Amazon Web Services

Apache Software Foundation, originally developed by HP

Initial release

2016

2008

2021

2014

Current release

5.3.6, November 2023

2.5.0, January 2023

2.3.0, February 2019

License

Commercial or Open Source

Open Source

AGPL v3

commercial

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache Version 2.0

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.

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Implementation language

Python

Java

C++, Java

Server operating systems

Linux

hosted

All OS with a Java VM

Linux

Data scheme

schema-free

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

yes

Typing

predefined data types such as float or date

yes, details here

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

the object must implement a serialization strategy

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language (GQL)

SQL-like query language

yes

APIs and other access methods

CLI Client
RESTful HTTP API

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

JCache
JPA
Memcached protocol
RESTful HTTP API

Java API
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

using Google App Engine

yes

Event Listeners, Executor Services

yes

Java Stored Procedures

Triggers

Callbacks using the Google Apps Engine

yes

Events

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication using Paxos

yes

Replicated Map

yes

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

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

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

one or two-phase-commit; repeatable reads; read commited

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

yes

In-memory capabilities

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

yes

User concepts

Access control

yes

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

Role-based access control

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

OpenSearch is a highly scalable and extensible open-source software suite for search,...
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Competitive advantages

Distributed as fully open source under Apache License, Version 2.0 (ALv2), OpenSearch...
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Typical application scenarios

The OpenSearch platform is used across a broad range of search , analytics, and observability...
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Licensing and pricing models

The OpenSearch Project offers open source software licensed under Apache License...
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