DBMS > Dgraph vs. Elasticsearch vs. Google Cloud Bigtable vs. MySQL vs. TypeDB

System Properties Comparison Dgraph vs. Elasticsearch vs. Google Cloud Bigtable vs. MySQL vs. TypeDB

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

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.

Widely used open source RDBMS

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

Primary database model

Graph DBMS

Search engine

Key-value store
Wide column store

Relational DBMS

Key/Value like access via memcached API

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Document store
Spatial DBMS

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

Score	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	132.83
Rank	#7	Overall
	#1	Search engines

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

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	0.70
Rank	#230	Overall
	#20	Graph DBMS
	#106	Relational DBMS

Website

dgraph.io

www.elastic.co/elasticsearch

cloud.google.com/bigtable

www.mysql.com

typedb.com

Technical documentation

dgraph.io/docs

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

cloud.google.com/bigtable/docs

dev.mysql.com/doc

typedb.com/docs

Developer

Dgraph Labs, Inc.

Elastic

Google

Oracle

since 2010, originally MySQL AB, then Sun

Vaticle

Initial release

2016

2010

2015

1995

2016

Current release

8.6, January 2023

8.4.0, April 2024

2.26.3, January 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Elastic License

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPL Version 3, commercial licenses available

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 and C++

Java

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

schema-free

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

schema-free

yes

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.

yes

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

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

Java API
RESTful HTTP/JSON API

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

ADO.NET
JDBC
ODBC
Proprietary native API

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

Supported programming languages

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

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

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

yes

proprietary syntax

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

by using Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

yes

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

Multi-source replication
Source-replica replication

Multi-source replication

by using Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

by using Apache Kafka and Apache Zookeeper

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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)

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

substituted by the relationship feature

Transaction concepts

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

ACID

Atomic single-row operations

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

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)

Users with fine-grained authorization concept

no user groups or roles

yes

at REST API level; other APIs in progress

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Licensing and pricing models

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