DBMS > CrateDB vs. Google Cloud Datastore vs. searchxml vs. SiriDB

System Properties Comparison CrateDB vs. Google Cloud Datastore vs. searchxml vs. SiriDB

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Editorial information provided by DB-Engines

Name

Description

Distributed Database based on Lucene

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

DBMS for structured and unstructured content wrapped with an application server

Open Source Time Series DBMS

Primary database model

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Document store

Native XML DBMS
Search engine

Time Series DBMS

Secondary database models

Relational 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	4.13
Rank	#71	Overall
	#12	Document stores

Score	0.00
Rank	#385	Overall
	#7	Native XML DBMS
	#24	Search engines

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Website

cratedb.com

cloud.google.com/datastore

www.searchxml.net/category/products

siridb.com

Technical documentation

cratedb.com/docs

cloud.google.com/datastore/docs

www.searchxml.net/support/handouts

docs.siridb.com

Developer

Crate

Google

informationpartners gmbh

Cesbit

Initial release

2013

2008

2015

2017

Current release

5.8.1, August 2024

1.0

License

Commercial or Open Source

Open Source

commercial

Open Source

MIT License

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

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

hosted

Windows

Linux

Data scheme

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

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, details here

yes

Numeric data

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, but no triggers and constraints, and PostgreSQL compatibility

SQL-like query language (GQL)

APIs and other access methods

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

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

RESTful HTTP API
WebDAV
XQuery
XSLT

HTTP API

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
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C++

most other programming languages supported via APIs

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

user defined functions (Javascript)

using Google App Engine

yes

on the application server

Triggers

Callbacks using the Google Apps Engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

Multi-source replication using Paxos

yes

sychronisation to multiple collections

yes

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

Eventual Consistency
Read-after-write consistency on record level

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

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

Serializable Isolation within Transactions, Read Committed outside of Transactions

multiple readers, single writer

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

rights management via user accounts

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

simple rights management via user accounts

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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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