DBMS > Apache Druid vs. Axibase vs. InfinityDB vs. STSdb

System Properties Comparison Apache Druid vs. Axibase vs. InfinityDB vs. STSdb

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Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

A Java embedded Key-Value Store which extends the Java Map interface

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Relational DBMS
Time Series DBMS

Time Series DBMS

Key-value store

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	0.29
Rank	#292	Overall
	#25	Time Series DBMS

Score	0.00
Rank	#378	Overall
	#57	Key-value stores

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

druid.apache.org

axibase.com/docs/atsd/finance

boilerbay.com

github.com/STSSoft/STSdb4

Technical documentation

druid.apache.org/docs/latest/design

boilerbay.com/infinitydb/manual

Developer

Apache Software Foundation and contributors

Axibase Corporation

Boiler Bay Inc.

STS Soft SC

Initial release

2012

2013

2002

2011

Current release

29.0.1, April 2024

15585

4.0

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache license v2

commercial

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

commercial

Open Source

GPLv2, commercial license available

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

Server operating systems

Linux
OS X
Unix

Linux

All OS with a Java VM

Windows

Data scheme

yes

schema-less columns are supported

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

Typing

predefined data types such as float or date

yes

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

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

yes

primitive types and user defined types (classes)

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

manual creation possible, using inversions based on multi-value capability

SQL

Support of SQL

SQL for querying

SQL-like query language

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

.NET Client API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Go
Java
PHP
Python
R
Ruby

Java

C#
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

READ-COMMITTED or SERIALIZED

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

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.

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

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