DBMS > CrateDB vs. IBM Db2 Event Store vs. MaxDB vs. Snowflake

System Properties Comparison CrateDB vs. IBM Db2 Event Store vs. MaxDB vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

Distributed Database based on Lucene

Distributed Event Store optimized for Internet of Things use cases

A robust and reliable RDBMS optimized to run all major SAP solutions

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

Event Store
Time Series DBMS

Relational 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	0.18
Rank	#315	Overall
	#2	Event Stores
	#26	Time Series DBMS

Score	2.15
Rank	#115	Overall
	#55	Relational DBMS

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Website

cratedb.com

www.ibm.com/products/db2-event-store

maxdb.sap.com

www.snowflake.com

Technical documentation

cratedb.com/docs

www.ibm.com/docs/en/db2-event-store

maxdb.sap.com/documentation

docs.snowflake.net/manuals/index.html

Developer

Crate

IBM

SAP, acquired from Software AG (Adabas-D) in 1997

Snowflake Computing Inc.

Initial release

2013

2017

1984

2014

Current release

5.8.1, August 2024

2.0

7.9.10.12, February 2024

License

Commercial or Open Source

Open Source

commercial

free developer edition available

commercial

Limited community edition free

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.

Implementation language

Java

C and C++

C++

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

Linux

Linux, macOS, Windows for the developer addition

AIX
HP-UX
Linux
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

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

yes

through the embedded Spark runtime

yes

APIs and other access methods

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

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
WebDAV

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

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

.Net
C#
Java
Perl
PHP
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions (Javascript)

yes

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

Active-active shard replication

Source-replica replication

yes

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

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

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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 access rights according to SQL-standard

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

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