DBMS > CrateDB vs. DataFS vs. PlanetScale vs. TinkerGraph

System Properties Comparison CrateDB vs. DataFS vs. PlanetScale vs. TinkerGraph

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Editorial information provided by DB-Engines

Name

Description

Distributed Database based on Lucene

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

Scalable, distributed, serverless MySQL database platform built on top of Vitess

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Object oriented DBMS

Relational DBMS

Graph DBMS

Secondary database models

Relational DBMS

Graph DBMS

Document store
Spatial DBMS

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

Score	0.69
Rank	#226	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#11	Vector DBMS

Score	0.02
Rank	#369	Overall
	#18	Object oriented DBMS

Score	1.09
Rank	#178	Overall
	#82	Relational DBMS

Score	0.08
Rank	#345	Overall
	#34	Graph DBMS

Website

cratedb.com

newdatabase.com

planetscale.com

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

cratedb.com/docs

dev.mobiland.com/Overview.xsp

planetscale.com/docs

Developer

Crate

Mobiland AG

PlanetScale

Initial release

2013

2018

2020

2009

Current release

5.8.1, August 2024

1.1.263, October 2022

License

Commercial or Open Source

Open Source

commercial

Open Source

Apache 2.0

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

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

Windows

Docker
Linux
macOS

Data scheme

Flexible Schema (defined schema, partial schema, schema free)

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

yes

with proprietary extensions

APIs and other access methods

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

.NET Client API
Proprietary client DLL
WinRT client

ADO.NET
JDBC
MySQL protocol
ODBC

TinkerPop 3

Supported programming languages

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

.Net
C
C#
C++
VB.Net

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Groovy
Java

Server-side scripts

Stored procedures

user defined functions (Javascript)

yes

proprietary syntax

Triggers

no, except callback-events from server when changes happened

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Proprietary Sharding system

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Read-after-write consistency on record level

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

none

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Relationships in graphs

Transaction concepts

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

unique row identifiers can be used for implementing an optimistic concurrency control strategy

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

optional

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

rights management via user accounts

Windows-Profile

Users with fine-grained authorization concept

no user groups or roles

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More resources

Recent citations in the news

CrateDB Appoints Jeff Olson as New CRO
9 July 2024, PR Newswire

CrateDB Announces Availability of CrateDB on Google Cloud Marketplace
8 April 2024, Datanami

Taleo Consulting and CrateDB Announce Strategic Partnership to Transform Data Management and Analytics in Financial Services markets
29 July 2024, PR Newswire

How We Designed CrateDB as a Realtime SQL DBMS for the Internet of Things
29 August 2017, The New Stack

CrateDB Appoints Sergey Gerasimenko as New CTO
19 February 2024, PR Newswire

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29 November 2023, SDTimes.com

PlanetScale forks MySQL to add vector support
3 October 2023, TechCrunch

Top Database as a Service (DBaaS) Startups
28 August 2024, Tracxn

PlanetScale review: Horizontally scalable MySQL in the cloud
1 September 2021, InfoWorld

provided by Google News

Unit testing Apache TinkerPop transactions: From TinkerGraph to Amazon Neptune
3 June 2024, AWS Blog

Simple Deployment of a Graph Database: JanusGraph
12 October 2020, Towards Data Science

Introducing Gremlin query hints for Amazon Neptune
26 February 2019, AWS Blog

provided by Google News

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