DBMS > CrateDB vs. IRONdb vs. Spark SQL vs. SQLite vs. Virtuoso

System Properties Comparison CrateDB vs. IRONdb vs. Spark SQL vs. SQLite vs. Virtuoso

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Distributed Database based on Lucene

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Spark SQL is a component on top of 'Spark Core' for structured data processing

Widely used embeddable, in-process RDBMS

Virtuoso is a multi-model hybrid-RDBMS that supports management of data represented as relational tables and/or property graphs

Primary database model

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Time Series DBMS

Relational DBMS

Document store
Graph DBMS
Native XML DBMS
Relational DBMS
RDF store
Search engine

Secondary database models

Relational DBMS

Spatial DBMS

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

Score	0.73
Rank	#224	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#8	Vector DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	4.26
Rank	#78	Overall
	#13	Document stores
	#4	Graph DBMS
	#2	Native XML DBMS
	#42	Relational DBMS
	#2	RDF stores
	#9	Search engines

Website

cratedb.com

www.circonus.com/solutions/time-series-database/

spark.apache.org/sql

www.sqlite.org

virtuoso.openlinksw.com

Technical documentation

cratedb.com/docs

docs.circonus.com/irondb/category/getting-started

spark.apache.org/docs/latest/sql-programming-guide.html

www.sqlite.org/docs.html

docs.openlinksw.com/virtuoso

Developer

Crate

Circonus LLC.

Apache Software Foundation

Dwayne Richard Hipp

OpenLink Software

Initial release

2013

2017

2014

2000

1998

Current release

V0.10.20, January 2018

3.5.0 ( 2.13), September 2023

3.45.3 (15 April 2024), April 2024

7.2.11, September 2023

License

Commercial or Open Source

Open Source

commercial

Open Source

Apache 2.0

Open Source

Public Domain

Open Source

GPLv2, extended commercial license available

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.

CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.

Implementation language

Java

C and C++

Scala

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

Linux

Linux
OS X
Windows

server-less

AIX
FreeBSD
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

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

schema-free

yes

dynamic column types

yes

SQL - Standard relational schema
RDF - Quad (S, P, O, G) or Triple (S, P, O)
XML - DTD, XML Schema
DAV - freeform filesystem objects, plus User Defined Types a/k/a Dynamic Extension Type

Typing

predefined data types such as float or date

yes

text, numeric, histograms

yes

not rigid because of 'dynamic typing' concept.

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

yes, but no triggers and constraints, and PostgreSQL compatibility

SQL-like query language (Circonus Analytics Query Language: CAQL)

SQL-like DML and DDL statements

yes

SQL-92 is not fully supported

yes

SQL-92, SQL-200x, SQL-3, SQLX

APIs and other access methods

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

HTTP API

JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

ADO.NET
GeoSPARQL
HTTP API
JDBC
Jena RDF API
ODBC
OLE DB
RDF4J API
RESTful HTTP API
Sesame REST HTTP Protocol
SOAP webservices
SPARQL 1.1
WebDAV
XPath
XQuery
XSLT

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++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

Java
Python
R
Scala

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

.Net
C
C#
C++
Java
JavaScript
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

user defined functions (Javascript)

yes, in Lua

yes

Virtuoso PL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic, metric affinity per node

yes, utilizing Spark Core

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

configurable replication factor, datacenter aware

none

Chain, star, and bi-directional replication
Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Read-after-write consistency on record level

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Foreign keys

Referential integrity

yes

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

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

Fine-grained Attribute-Based Access Control (ABAC) in addition to typical coarse-grained Role-Based Access Control (RBAC) according to SQL-standard. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)

More information provided by the system vendor

Specific characteristics

The enterprise database for time series, documents, and vectors. Distributed - Native...
» more

Virtuoso is a modern multi-model RDBMS for managing data represented as tabular relations...
» more

Competitive advantages

Response time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more

Performance & Scale — as exemplified by DBpedia and the LOD Cloud it spawned, i.e.,...
» more

Typical application scenarios

IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more

Used for — Analytics/BI Conceptual Data Virtualization Enterprise Knowledge Graphs...
» more

Key customers

Across all continents, CrateDB is used by companies of all sizes to meet the most...
» more

Broad use across enterprises and governments including — European Union (EU) US Government...
» more

Market metrics

The CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more

Largest installed-base of Multi-Model RDBMS for AI-friendly Knowledge Graphs Platform...
» more

Licensing and pricing models

See CrateDB pricing >
» more

Available in both Commercial Enterprise and Open Source (GPL v2) Editions Feature...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.