DBMS > CockroachDB vs. Google Cloud Datastore vs. Oracle NoSQL vs. RocksDB vs. SAP SQL Anywhere

System Properties Comparison CockroachDB vs. Google Cloud Datastore vs. Oracle NoSQL vs. RocksDB vs. SAP SQL Anywhere

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

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Relational DBMS

Document store

Document store
Key-value store
Relational DBMS

Key-value store

Relational DBMS

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	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Website

www.cockroachlabs.com

cloud.google.com/datastore

www.oracle.com/database/nosql/technologies/nosql

rocksdb.org

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

www.cockroachlabs.com/docs

cloud.google.com/datastore/docs

docs.oracle.com/en/database/other-databases/nosql-database/index.html

github.com/facebook/rocksdb/wiki

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Cockroach Labs

Google

Oracle

Facebook, Inc.

SAP

formerly Sybase

Initial release

2015

2008

2011

2013

1992

Current release

23.1.1, May 2023

23.3, December 2023

8.11.4, April 2024

17, July 2015

License

Commercial or Open Source

Open Source

Apache 2.0, commercial license available

commercial

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

BSD

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.

Implementation language

Java

C++

Server operating systems

Linux
macOS
Windows

hosted

Linux
Solaris SPARC/x86

Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

dynamic schema

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, details here

optional

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)

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC

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

RESTful HTTP API

C++ API
Java API

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

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

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

C
C#
Go
Java
JavaScript (Node.js)
Python

C
C++
Go
Java
Perl
Python
Ruby

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

Server-side scripts

Stored procedures

using Google App Engine

yes, in C/C++, Java, .Net or Perl

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

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using RAFT

Multi-source replication using Paxos

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

yes

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

with Hadoop integration

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.

Eventual Consistency
Immediate Consistency

depending on configuration

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

configurable

ACID within a storage node (=shard)

yes

ACID

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

off heap cache

yes

User concepts

Access control

Role-based access control

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

Access rights for users and roles

fine grained access rights according to SQL-standard

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