DBMS > CrateDB vs. EXASOL vs. Google Cloud Spanner vs. Kdb vs. Snowflake

System Properties Comparison CrateDB vs. EXASOL vs. Google Cloud Spanner vs. Kdb vs. Snowflake

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.

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

High performance Time Series DBMS

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

Primary database model

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Relational DBMS

Time Series DBMS
Vector DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.73
Rank	#229	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#8	Vector DBMS

Score	2.25
Rank	#120	Overall
	#57	Relational DBMS

Score	2.89
Rank	#105	Overall
	#53	Relational DBMS

Score	7.70
Rank	#53	Overall
	#3	Time Series DBMS
	#1	Vector DBMS

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Website

cratedb.com

www.exasol.com

cloud.google.com/spanner

kx.com

www.snowflake.com

Technical documentation

cratedb.com/docs

www.exasol.com/resources

cloud.google.com/spanner/docs

code.kx.com

docs.snowflake.net/manuals/index.html

Developer

Crate

Exasol

Google

Kx Systems, a division of First Derivatives plc

Snowflake Computing Inc.

Initial release

2013

2000

2017

2000

kdb was released 2000, kdb+ in 2003

2014

Current release

3.6, May 2018

License

Commercial or Open Source

Open Source

commercial

free 32-bit version

commercial

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.

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

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

hosted

Linux
OS X
Solaris
Windows

hosted

Data scheme

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

yes

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

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

table attribute 'grouped'

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

yes

Query statements complying to ANSI 2011

SQL-like query language (q)

yes

APIs and other access methods

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

.Net
JDBC
ODBC
WebSocket

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

CLI Client
JDBC
ODBC

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

Go
Java
JavaScript (Node.js)
Python

C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions (Javascript)

user defined functions

Triggers

yes

with views

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

Multi-source replication with 3 replicas for regional instances.

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

yes

using Google Cloud Dataflow

similar paradigm used for internal processing

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Read-after-write consistency on record level

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on 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

Strict serializable isolation

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

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

rights management via user accounts

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

More information provided by the system vendor

Specific characteristics

The enterprise database for time series, documents, and vectors. Distributed - Native...
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Integrated columnar database & programming system for streaming, real time and historical...
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Competitive advantages

Response time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
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provides seamless scalability; runs on industry standard server platforms; is top-ranked...
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Typical application scenarios

IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
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tick database streaming sensor data massive intelligence applications oil and gas...
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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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Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
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Market metrics

The CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
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kdb+ performance and reliability proven by our customers in critical infrastructure...
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Licensing and pricing models

See CrateDB pricing >
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upon request
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.