DBMS > AlaSQL vs. CockroachDB vs. Google BigQuery vs. MySQL vs. SAP SQL Anywhere

System Properties Comparison AlaSQL vs. CockroachDB vs. Google BigQuery vs. MySQL vs. SAP SQL Anywhere

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

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

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

Primary database model

Document store
Relational DBMS

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Website

alasql.org

www.cockroachlabs.com

cloud.google.com/bigquery

www.mysql.com

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

Technical documentation

github.com/AlaSQL/alasql

www.cockroachlabs.com/docs

cloud.google.com/bigquery/docs

dev.mysql.com/doc

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Andrey Gershun & Mathias R. Wulff

Cockroach Labs

Google

Oracle

since 2010, originally MySQL AB, then Sun

SAP

formerly Sybase

Initial release

2014

2015

2010

1995

1992

Current release

23.1.1, May 2023

8.3.0, January 2024

17, July 2015

License

Commercial or Open Source

Open Source

MIT-License

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

JavaScript

C and C++

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

Linux
macOS
Windows

hosted

FreeBSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

schema-free

dynamic schema

yes

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

Close to SQL99, but no user access control, stored procedures and host language bindings.

yes, wire compatible with PostgreSQL

yes

with proprietary extensions

yes

APIs and other access methods

JavaScript API

JDBC

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

JavaScript

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

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

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

proprietary syntax

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication using RAFT

Multi-source replication
Source-replica replication

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

yes

only for local storage and DOM-storage

ACID

Since BigQuery is designed for querying data

ACID

not for MyISAM storage engine

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

by using IndexedDB, SQL.JS or proprietary FileStorage

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

fine grained access rights according to SQL-standard

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