DBMS > Axibase vs. IBM Db2 Event Store vs. Oracle NoSQL vs. XTDB

System Properties Comparison Axibase vs. IBM Db2 Event Store vs. Oracle NoSQL vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

Distributed Event Store optimized for Internet of Things use cases

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Time Series DBMS

Event Store
Time Series DBMS

Document store
Key-value store
Relational DBMS

Document store

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

Score	0.35
Rank	#282	Overall
	#25	Time Series DBMS

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

axibase.com/docs/atsd/finance

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

www.oracle.com/database/nosql/technologies/nosql

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

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

docs.oracle.com/en/database/other-databases/nosql-database/index.html

www.xtdb.com/docs

Developer

Axibase Corporation

IBM

Oracle

Juxt Ltd.

Initial release

2013

2017

2011

2019

Current release

15585

2.0

24.1, May 2024

1.19, September 2021

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

commercial

free developer edition available

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

MIT License

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.

Implementation language

Java

C and C++

Java

Clojure

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Linux
Solaris SPARC/x86

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

schema-free

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

yes

optional

yes, extensible-data-notation format

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

SQL-like query language

yes

through the embedded Spark runtime

SQL-like DML and DDL statements

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

RESTful HTTP API

HTTP REST
JDBC

Supported programming languages

Go
Java
PHP
Python
R
Ruby

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)
Python

Clojure
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Active-active shard replication

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

configurable

ACID within a storage node (=shard)

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

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

off heap cache

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

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