DBMS > BaseX vs. Google Cloud Datastore vs. RocksDB vs. SAP SQL Anywhere vs. YDB

System Properties Comparison BaseX vs. Google Cloud Datastore vs. RocksDB vs. SAP SQL Anywhere vs. YDB

Editorial information provided by DB-Engines

Name

Description

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

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

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

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

Document store
Relational DBMS

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

Score	1.84
Rank	#135	Overall
	#4	Native XML DBMS

Score	4.36
Rank	#72	Overall
	#12	Document stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Score	0.33
Rank	#287	Overall
	#43	Document stores
	#132	Relational DBMS

Website

basex.org

cloud.google.com/datastore

rocksdb.org

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

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

Technical documentation

docs.basex.org

cloud.google.com/datastore/docs

github.com/facebook/rocksdb/wiki

help.sap.com/docs/SAP_SQL_Anywhere

ydb.tech/en/docs

Developer

BaseX GmbH

Google

Facebook, Inc.

SAP

formerly Sybase

Yandex

Initial release

2007

2008

2013

1992

2019

Current release

11.0, June 2024

9.2.1, May 2024

17, July 2015

License

Commercial or Open Source

Open Source

BSD license

commercial

Open Source

BSD

commercial

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

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

Server operating systems

Linux
OS X
Windows

hosted

Linux

AIX
HP-UX
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

XQuery supports types

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

SQL-like query language (GQL)

yes

SQL-like query language (YQL)

APIs and other access methods

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

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

C++ API
Java API

ADO.NET
HTTP API
JDBC
ODBC

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

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

C
C++
Go
Java
Perl
Python
Ruby

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

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

yes

using Google App Engine

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

Triggers

yes

via events

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication using Paxos

yes

Source-replica replication

Database mirroring

Active-passive shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

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

multiple readers, single writer

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

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

User concepts

Access control

Users with fine-grained authorization concept on 4 levels

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

fine grained access rights according to SQL-standard

Access rights defined for Yandex Cloud users

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