DBMS > Heroic vs. Kdb vs. OrigoDB vs. XTDB

System Properties Comparison Heroic vs. Kdb vs. OrigoDB vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

High performance Time Series DBMS

A fully ACID in-memory object graph database

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

Primary database model

Time Series DBMS

Time Series DBMS
Vector DBMS

Document store
Object oriented DBMS

Document store

Secondary database models

Relational DBMS

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

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	7.71
Rank	#49	Overall
	#2	Time Series DBMS
	#1	Vector DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

github.com/spotify/heroic

kx.com

origodb.com

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

Technical documentation

spotify.github.io/heroic

code.kx.com

origodb.com/docs

www.xtdb.com/docs

Developer

Spotify

Kx Systems, a division of First Derivatives plc

Robert Friberg et al

Juxt Ltd.

Initial release

2014

2000

kdb was released 2000, kdb+ in 2003

2009

under the name LiveDB

2019

Current release

3.6, May 2018

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free 32-bit version

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

Clojure

Server operating systems

Linux
OS X
Solaris
Windows

Linux
Windows

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

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

yes

can be achieved using .NET

Secondary indexes

yes

via Elasticsearch

yes

table attribute 'grouped'

yes

SQL

Support of SQL

SQL-like query language (q)

limited SQL, making use of Apache Calcite

APIs and other access methods

HQL (Heroic Query Language, a JSON-based language)
HTTP API

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

.NET Client API
HTTP API
LINQ

HTTP REST
JDBC

Supported programming languages

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

.Net

Clojure
Java

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

with views

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

client side managed; servers are not synchronized

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

similar paradigm used for internal processing

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

depending on model

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

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

User concepts

Access control

rights management via user accounts

Role based authorization

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
» more

Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more

Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
» more

Key customers

Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more

Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
» more

Licensing and pricing models

upon request
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

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