DBMS > CockroachDB vs. Google BigQuery vs. MySQL vs. Oracle Coherence vs. TempoIQ

System Properties Comparison CockroachDB vs. Google BigQuery vs. MySQL vs. Oracle Coherence vs. TempoIQ

Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

Large scale data warehouse service with append-only tables

Widely used open source RDBMS

Oracles in-memory data grid solution

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Primary database model

Relational DBMS

Key/Value like access via memcached API

Key-value store

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	5.73
Rank	#58	Overall
	#34	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	1.97
Rank	#129	Overall
	#22	Key-value stores

Website

www.cockroachlabs.com

cloud.google.com/bigquery

www.mysql.com

www.oracle.com/java/coherence

tempoiq.com (offline)

Technical documentation

www.cockroachlabs.com/docs

cloud.google.com/bigquery/docs

dev.mysql.com/doc

docs.oracle.com/en/middleware/standalone/coherence

Developer

Cockroach Labs

Google

Oracle

since 2010, originally MySQL AB, then Sun

Oracle

TempoIQ

Initial release

2015

2010

1995

2007

2012

Current release

24.1.0, May 2024

8.4.0, April 2024

14.1, August 2023

License

Commercial or Open Source

Open Source

Apache 2.0, commercial license available

commercial

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

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Implementation language

C and C++

Java

Server operating systems

Linux
macOS
Windows

hosted

FreeBSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

Data scheme

dynamic schema

yes

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, wire compatible with PostgreSQL

yes

with proprietary extensions

APIs and other access methods

JDBC

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
Proprietary native API

JCache
JPA
RESTful HTTP API

HTTP API

Supported programming languages

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

.Net
Java
JavaScript
Objective-C
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

.Net
C++
Java

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

proprietary syntax

Triggers

yes

Live Events

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using RAFT

Multi-source replication
Source-replica replication

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

not for MyISAM storage engine

configurable

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

optionally

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

Role-based access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Users with fine-grained authorization concept

no user groups or roles

authentification to access the cache via certificates or http basic authentication

simple authentication-based access control

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