DBMS > Apache Impala vs. GraphDB vs. GridDB vs. MySQL vs. TDSQL for MySQL

System Properties Comparison Apache Impala vs. GraphDB vs. GridDB vs. MySQL vs. TDSQL for MySQL

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Enterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL.

Scalable in-memory time series database optimized for IoT and Big Data

Widely used open source RDBMS

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

Primary database model

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Document store

Key-value store
Relational DBMS

Document store
Spatial DBMS

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	3.25
Rank	#91	Overall
	#7	Graph DBMS
	#4	RDF stores

Score	2.09
Rank	#120	Overall
	#10	Time Series DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	0.85
Rank	#207	Overall
	#97	Relational DBMS

Website

www.tencentcloud.com/products/dcdb

Technical documentation

impala.apache.org/impala-docs.html

graphdb.ontotext.com/documentation

docs.griddb.net

dev.mysql.com/doc

www.tencentcloud.com/document/product/1042

Social network pages

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Ontotext

Toshiba Corporation

Oracle

since 2010, originally MySQL AB, then Sun

Tencent

Initial release

2013

2000

2013

1995

2013

Current release

4.1.0, June 2022

10.4, October 2023

5.1, August 2022

8.4.0, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Some plugins of GraphDB Workbench are open sourced

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

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.

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Implementation language

C++

Java

C++

C and C++

Server operating systems

Linux

All OS with a Java VM
Linux
OS X
Windows

Linux

FreeBSD
Linux
OS X
Solaris
Windows

hosted

Data scheme

yes

schema-free and OWL/RDFS-schema support; RDF shapes

yes

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

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

yes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC

SQL92, SQL-like TQL (Toshiba Query Language)

yes

with proprietary extensions

yes

APIs and other access methods

JDBC
ODBC

GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

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

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

C
C#
C++
Java
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

well-defined plugin interfaces; JavaScript server-side extensibility

yes

proprietary syntax

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

Foreign keys

Referential integrity

yes

Constraint checking

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at container level

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.

yes

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Default Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on.

Access rights for users can be defined per database

Users with fine-grained authorization concept

no user groups or roles

Users with fine-grained authorization concept

More information provided by the system vendor

Specific characteristics

Ontotext GraphDB is a semantic database engine that allows organizations to build...
» more

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

Competitive advantages

GraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment...
» more

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

Typical application scenarios

Metadata enrichment and management, linked data publishing, semantic inferencing...
» more

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

Key customers

GraphDB provides a platform for building next-generation AI and Knowledge Graph...
» more

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Market metrics

GraphDB is the most utilized semantic triplestore for mission-critical enterprise...
» more

GitHub trending repository
» more

Licensing and pricing models

GraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition...
» more

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

News

Riding the Databricks Wave with Hybrid Knowledge Graphs
6 June 2024

Matching Skills and Candidates with Graph RAG
31 May 2024

A Triple Store RAG Retriever
29 May 2024

Integrating GraphDB with Relational Database Systems
23 May 2024

Understanding the Graph Center of Excellence
17 May 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.