DBMS > CrateDB vs. NSDb vs. UniData,UniVerse vs. XTDB

System Properties Comparison CrateDB vs. NSDb vs. UniData,UniVerse vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

Distributed Database based on Lucene

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

MultiValue database and application server with SQL mapping layer and meta database capabilities

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Time Series DBMS

Multivalue DBMS

Document store

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	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	2.25
Rank	#112	Overall
	#2	Multivalue DBMS

Score	0.13
Rank	#330	Overall
	#45	Document stores

Website

cratedb.com

nsdb.io

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

cratedb.com/docs

nsdb.io/Architecture

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

www.xtdb.com/docs

Developer

Crate

Rocket Software

Juxt Ltd.

Initial release

2013

2017

1985

2019

Current release

5.8.1, August 2024

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

MIT License

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Java, Scala

Clojure

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

Linux
macOS

AIX
HP-UX
Linux
Solaris
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

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

schema-free

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

optional

yes, extensible-data-notation format

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

all fields are automatically indexed

yes

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

SQL-like query language

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

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

gRPC
HTTP REST
WebSocket

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

HTTP REST
JDBC

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

Java
Scala

.Net
Basic

U2 Basic
C
Java

Clojure
Java

Server-side scripts

Stored procedures

user defined functions (Javascript)

yes

Triggers

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

Source-replica replication

yes, each node contains all data

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

Eventual Consistency

Foreign keys

Referential integrity

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

configurable

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

User concepts

Access control

rights management via user accounts

Access rights according to SQL-standard and operating system based

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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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