DBMS > Dgraph vs. Google Cloud Bigtable vs. HBase vs. OpenSearch vs. RocksDB

System Properties Comparison Dgraph vs. Google Cloud Bigtable vs. HBase vs. OpenSearch vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

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

Wide-column store based on Apache Hadoop and on concepts of BigTable

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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Graph DBMS

Key-value store
Wide column store

Wide column store

Search engine

Key-value store

Secondary database models

Vector DBMS

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

Score	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	16.03
Rank	#37	Overall
	#4	Search engines

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

dgraph.io

cloud.google.com/bigtable

hbase.apache.org

github.com/opensearch-project
opensearch.org

rocksdb.org

Technical documentation

dgraph.io/docs

cloud.google.com/bigtable/docs

hbase.apache.org/book.html

opensearch.org/docs/latest

github.com/facebook/rocksdb/wiki

Developer

Dgraph Labs, Inc.

Google

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Amazon Web Services

Facebook, Inc.

Initial release

2016

2015

2008

2021

2013

Current release

2.3.4, January 2021

2.5.0, January 2023

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache version 2

Open Source

Apache Version 2.0

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

Linux
OS X
Windows

hosted

Linux
Unix
Windows

using Cygwin

All OS with a Java VM

Linux

Data scheme

schema-free

schema-free, schema definition possible

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

options to bring your own types, AVRO

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

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

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

Java API
RESTful HTTP API
Thrift

Java API
RESTful HTTP/JSON API

C++ API
Java API

Supported programming languages

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

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

C
C#
C++
Groovy
Java
PHP
Python
Scala

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Coprocessors in Java

yes

Triggers

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

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

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Immediate Consistency or Eventual Consistency

Eventual Consistency

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

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Atomic single-row operations

Single row ACID (across millions of columns)

yes

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

User concepts

Access control

Planned for future releases

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

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

More information provided by the system vendor

Specific characteristics

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

Competitive advantages

Distributed as fully open source under Apache License, Version 2.0 (ALv2), OpenSearch...
» more

Typical application scenarios

The OpenSearch platform is used across a broad range of search , analytics, and observability...
» more

Licensing and pricing models

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

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