DBMS > Google Cloud Bigtable vs. MySQL vs. Splunk vs. Trafodion vs. YDB

System Properties Comparison Google Cloud Bigtable vs. MySQL vs. Splunk vs. Trafodion vs. YDB

Editorial information provided by DB-Engines

Name

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

Description

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

Analytics Platform for Big Data

Transactional SQL-on-Hadoop DBMS

A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API

Primary database model

Key-value store
Wide column store

Relational DBMS

Key/Value like access via memcached API

Search engine

Relational DBMS

Document store
Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	86.45
Rank	#14	Overall
	#2	Search engines

Score	0.35
Rank	#278	Overall
	#43	Document stores
	#127	Relational DBMS

Website

cloud.google.com/bigtable

www.mysql.com

www.splunk.com

trafodion.apache.org

github.com/ydb-platform/ydb
ydb.tech

Technical documentation

cloud.google.com/bigtable/docs

dev.mysql.com/doc

docs.splunk.com/Documentation/Splunk

trafodion.apache.org/documentation.html

ydb.tech/en/docs

Developer

Google

Oracle

since 2010, originally MySQL AB, then Sun

Splunk Inc.

Apache Software Foundation, originally developed by HP

Yandex

Initial release

2015

1995

2003

2014

2019

Current release

8.4.0, April 2024

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Limited free edition and free developer edition available

Open Source

Apache 2.0

Open Source

Apache 2.0; commercial license 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

C and C++

C++, Java

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Solaris
Windows

Linux

Data scheme

schema-free

yes

Flexible Schema (defined schema, partial schema, schema free)

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

SQL

Support of SQL

yes

with proprietary extensions

Splunk Search Processing Language for search commands

yes

SQL-like query language (YQL)

APIs and other access methods

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

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP REST

ADO.NET
JDBC
ODBC

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

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

C#
Java
JavaScript
PHP
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

yes

proprietary syntax

yes

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication
Source-replica replication

Multi-source replication

yes, via HBase

Active-passive shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

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

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

Atomic single-row operations

ACID

not for MyISAM storage engine

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

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 Google Cloud Identity and Access Management (IAM)

Users with fine-grained authorization concept

no user groups or roles

Access rights for users and roles

fine grained access rights according to SQL-standard

Access rights defined for Yandex Cloud users

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