DBMS > Google Cloud Datastore vs. RocksDB vs. searchxml vs. TypeDB vs. Valentina Server

System Properties Comparison Google Cloud Datastore vs. RocksDB vs. searchxml vs. TypeDB vs. Valentina Server

Editorial information provided by DB-Engines

Name

Description

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)

DBMS for structured and unstructured content wrapped with an application server

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

Object-relational database and reports server

Primary database model

Document store

Key-value store

Native XML DBMS
Search engine

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

Relational DBMS

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

Score	4.36
Rank	#72	Overall
	#12	Document stores

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

Score	0.03
Rank	#390	Overall
	#7	Native XML DBMS
	#24	Search engines

Score	0.70
Rank	#230	Overall
	#20	Graph DBMS
	#106	Relational DBMS

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

cloud.google.com/datastore

rocksdb.org

www.searchxml.net/category/products

typedb.com

www.valentina-db.net

Technical documentation

cloud.google.com/datastore/docs

github.com/facebook/rocksdb/wiki

www.searchxml.net/support/handouts

typedb.com/docs

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Google

Facebook, Inc.

informationpartners gmbh

Vaticle

Paradigma Software

Initial release

2008

2013

2015

2016

1999

Current release

9.2.1, May 2024

1.0

2.26.3, January 2024

5.7.5

License

Commercial or Open Source

commercial

Open Source

BSD

commercial

Open Source

GPL Version 3, commercial licenses available

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

C++

Java

Server operating systems

hosted

Linux

Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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

APIs and other access methods

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

C++ API
Java API

RESTful HTTP API
WebDAV
XQuery
XSLT

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

ODBC

Supported programming languages

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

C
C++
Go
Java
Perl
Python
Ruby

C++

most other programming languages supported via APIs

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

using Google App Engine

yes

on the application server

yes

Triggers

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

Sharding

by using Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

yes

sychronisation to multiple collections

Multi-source replication

by using Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

by using Apache Kafka and Apache Zookeeper

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

substituted by the relationship feature

yes

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

yes

multiple readers, single writer

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

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

Domain, group and role-based access control at the document level and for application services

yes

at REST API level; other APIs in progress

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

TypeDB is a polymorphic database with a conceptual data model, a strong subtyping...
» more

Competitive advantages

TypeDB provides a new level of expressivity, extensibility, interoperability, and...
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Typical application scenarios

Life sciences : TypeDB makes working with biological data much easier and accelerates...
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Licensing and pricing models

Apache f or language drivers, and AGPL and Commercial for the database server. The...
» more

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