DBMS > CockroachDB vs. Google Cloud Datastore vs. Memcached vs. Oracle

System Properties Comparison CockroachDB vs. Google Cloud Datastore vs. Memcached vs. Oracle

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Editorial information provided by DB-Engines

Name

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.

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

In-memory key-value store, originally intended for caching

Widely used RDBMS

Primary database model

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	19.42
Rank	#32	Overall
	#4	Key-value stores

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Website

www.cockroachlabs.com

cloud.google.com/datastore

www.memcached.org

www.oracle.com/database

Technical documentation

www.cockroachlabs.com/docs

cloud.google.com/datastore/docs

github.com/memcached/memcached/wiki

docs.oracle.com/en/database

Developer

Cockroach Labs

Google

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Oracle

Initial release

2015

2008

2003

1980

Current release

24.1.0, May 2024

1.6.27, May 2024

23c, September 2023

License

Commercial or Open Source

Open Source

Apache 2.0, commercial license available

commercial

Open Source

BSD license

commercial

restricted free version is available

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.

Implementation language

C and C++

Server operating systems

Linux
macOS
Windows

hosted

FreeBSD
Linux
OS X
Unix
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Data scheme

dynamic schema

schema-free

yes

Schemaless in JSON and XML columns

Typing

predefined data types such as float or date

yes

yes, details here

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

SQL-like query language (GQL)

yes

with proprietary extensions

APIs and other access methods

JDBC

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

Proprietary protocol

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

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

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Server-side scripts

Stored procedures

using Google App Engine

PL/SQL

also stored procedures in Java possible

Triggers

Callbacks using the Google Apps Engine

yes

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

Sharding

none

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using RAFT

Multi-source replication using Paxos

none

Repcached, a Memcached patch, provides this functionallity

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

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

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

Role-based access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

yes

using SASL (Simple Authentication and Security Layer) protocol

fine grained access rights according to SQL-standard

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