DBMS > CrateDB vs. IBM Db2 Event Store vs. JaguarDB vs. Oracle Rdb

System Properties Comparison CrateDB vs. IBM Db2 Event Store vs. JaguarDB vs. Oracle Rdb

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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

Performant, highly scalable DBMS for AI and IoT applications

Primary database model

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Event Store
Time Series DBMS

Key-value store
Vector 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	0.00
Rank	#385	Overall
	#61	Key-value stores
	#16	Vector DBMS

Score	1.04
Rank	#184	Overall
	#84	Relational DBMS

Website

cratedb.com

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

www.jaguardb.com

www.oracle.com/database/technologies/related/rdb.html

Technical documentation

cratedb.com/docs

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

www.jaguardb.com/support.html

www.oracle.com/database/technologies/related/rdb-doc.html

Developer

Crate

IBM

DataJaguar, Inc.

Oracle, originally developed by Digital Equipment Corporation (DEC)

Initial release

2013

2017

2015

1984

Current release

5.8.1, August 2024

2.0

3.3 July 2023

7.4.1.1, 2021

License

Commercial or Open Source

Open Source

commercial

free developer edition available

Open Source

GPL V3.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C and C++

C++

the server part. Clients available in other languages

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

Linux

Linux, macOS, Windows for the developer addition

Linux

HP Open VMS

Data scheme

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

yes

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

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.

Secondary indexes

yes

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

yes

through the embedded Spark runtime

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

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

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

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

Server-side scripts

Stored procedures

user defined functions (Javascript)

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

Active-active shard replication

Multi-source replication

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

yes, on a single node

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

rights management via user accounts

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More resources

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