DBMS > CrateDB vs. EXASOL vs. JaguarDB vs. Snowflake vs. Vertica

System Properties Comparison CrateDB vs. EXASOL vs. JaguarDB vs. Snowflake vs. Vertica

Editorial information provided by DB-Engines

Name

Description

Distributed Database based on Lucene

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Performant, highly scalable DBMS for AI and IoT applications

Cloud-based data warehousing service for structured and semi-structured data

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Relational DBMS

Key-value store
Vector DBMS

Relational DBMS

Column oriented

Secondary database models

Relational DBMS

Spatial DBMS
Time Series 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	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	10.68
Rank	#43	Overall
	#27	Relational DBMS

Website

Technical documentation

cratedb.com/docs

www.exasol.com/resources

www.jaguardb.com/support.html

docs.snowflake.net/manuals/index.html

vertica.com/documentation

Developer

Crate

Exasol

DataJaguar, Inc.

Snowflake Computing Inc.

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2013

2000

2015

2014

2005

Current release

3.3 July 2023

12.0.3, January 2023

License

Commercial or Open Source

Open Source

commercial

Open Source

GPL V3.0

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

yes

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

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++

the server part. Clients available in other languages

C++

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

Linux

hosted

Linux

Data scheme

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

yes

support of semi-structured data formats (JSON, XML, Avro)

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

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.

yes

Secondary indexes

yes

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

yes

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

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

.Net
JDBC
ODBC
WebSocket

JDBC
ODBC

CLI Client
JDBC
ODBC

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

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
Lua
Python
R

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

JavaScript (Node.js)
Python

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

Server-side scripts

Stored procedures

user defined functions (Javascript)

user defined functions

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

similar concept for controling cloud resources

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

Multi-source replication

yes

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Read-after-write consistency on record level

Immediate Consistency

Eventual Consistency

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

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 according to SQL-standard

rights management via user accounts

Users with fine-grained authorization concept, user roles and pluggable authentication

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

Specific characteristics

The enterprise database for time series, documents, and vectors. Distributed - Native...
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Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantages

Response time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
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Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenarios

IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
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Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customers

Across all continents, CrateDB is used by companies of all sizes to meet the most...
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Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Market metrics

The CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
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Licensing and pricing models

See CrateDB pricing >
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Cost-based models and subscription-based models are both available. One license is...
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