DBMS > Blazegraph vs. GridDB vs. Microsoft Azure Table Storage vs. MySQL vs. ScyllaDB

System Properties Comparison Blazegraph vs. GridDB vs. Microsoft Azure Table Storage vs. MySQL vs. ScyllaDB

Editorial information provided by DB-Engines

Name

Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.

Description

High-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.

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

A Wide Column Store for rapid development using massive semi-structured datasets

Widely used open source RDBMS

Cassandra and DynamoDB compatible wide column store

Primary database model

Key/Value like access via memcached API

Wide column store

Secondary database models

Key-value store
Relational DBMS

Document store
Spatial DBMS

Key-value store

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

Score	0.81
Rank	#213	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	2.09
Rank	#120	Overall
	#10	Time Series DBMS

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	4.08
Rank	#76	Overall
	#5	Wide column stores

Website

blazegraph.com

griddb.net

azure.microsoft.com/en-us/services/storage/tables

www.mysql.com

www.scylladb.com

Technical documentation

Developer

Blazegraph

Toshiba Corporation

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

ScyllaDB

Initial release

2006

2013

2012

1995

2015

Current release

2.1.5, March 2019

5.1, August 2022

8.4.0, April 2024

ScyllaDB Open Source 5.4.1, January 2024

License

Commercial or Open Source

Open Source

extended commercial license available

Open Source

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

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Open Source (AGPL), commercial license available

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C++

C and C++

C++

Server operating systems

Linux
OS X
Windows

Linux

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

schema-free

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

RDF literal types

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

cluster global secondary indices

SQL

Support of SQL

SPARQL is used as query language

SQL92, SQL-like TQL (Toshiba Query Language)

yes

with proprietary extensions

SQL-like DML and DDL statements (CQL)

APIs and other access methods

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Proprietary protocol (CQL)

compatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift

Supported programming languages

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

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

.Net
C#
C++
Java
JavaScript (Node.js)
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

For CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala
For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby

Server-side scripts

Stored procedures

yes

proprietary syntax

yes, Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Multi-source replication
Source-replica replication

selectable replication factor

Representation of geographical distribution of servers is possible

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Immediate Consistency or Eventual Consistency depending on configuration

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Foreign keys

Referential integrity

yes

Relationships in Graphs

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at container level

optimistic locking

ACID

not for MyISAM storage engine

Atomicity and isolation are supported for single operations

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

in-memory tables

User concepts

Access control

Security and Authentication via Web Application Container (Tomcat, Jetty)

Access rights for users can be defined per database

Access rights based on private key authentication or shared access signatures

Users with fine-grained authorization concept

no user groups or roles

Access rights for users can be defined per object

More information provided by the system vendor

Specific characteristics

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

ScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
» more

Competitive advantages

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

Highly-performant (efficiently utilizes full resources of a node and network; millions...
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Typical application scenarios

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

ScyllaDB is ideal for applications that require high throughput and low latency at...
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Key customers

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

Discord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
» more

Market metrics

GitHub trending repository
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ScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
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Licensing and pricing models

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

ScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based...
» more

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