DBMS > IRONdb vs. Kinetica vs. Rockset vs. SAP SQL Anywhere vs. SQLite

System Properties Comparison IRONdb vs. Kinetica vs. Rockset vs. SAP SQL Anywhere vs. SQLite

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Fully vectorized database across both GPUs and CPUs

A scalable, reliable search and analytics service in the cloud, built on RocksDB

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Widely used embeddable, in-process RDBMS

Primary database model

Secondary database models

Spatial DBMS
Time Series DBMS

Relational DBMS
Search engine

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

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	0.82
Rank	#212	Overall
	#36	Document stores

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

www.circonus.com/solutions/time-series-database/

www.kinetica.com

rockset.com

www.sap.com/products/technology-platform/sql-anywhere.html

www.sqlite.org

Technical documentation

docs.circonus.com/irondb/category/getting-started

docs.kinetica.com

docs.rockset.com

help.sap.com/docs/SAP_SQL_Anywhere

www.sqlite.org/docs.html

Developer

Circonus LLC.

Kinetica

Rockset

SAP

formerly Sybase

Dwayne Richard Hipp

Initial release

2017

2012

2019

1992

2000

Current release

V0.10.20, January 2018

7.1, August 2021

17, July 2015

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Open Source

Public Domain

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

C and C++

C, C++

C++

Server operating systems

Linux

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows

server-less

Data scheme

schema-free

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

text, numeric, histograms

yes

dynamic typing

yes

not rigid because of 'dynamic typing' concept.

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.

ingestion from XML files supported

yes

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language (Circonus Analytics Query Language: CAQL)

SQL-like DML and DDL statements

Read-only SQL queries, including JOINs

yes

SQL-92 is not fully supported

APIs and other access methods

HTTP API

JDBC
ODBC
RESTful HTTP API

HTTP REST

ADO.NET
HTTP API
JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

C++
Java
JavaScript (Node.js)
Python

Go
Java
JavaScript (Node.js)
Python

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes, in Lua

user defined functions

yes, in C/C++, Java, .Net or Perl

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic, metric affinity per node

Sharding

Automatic sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware

Source-replica replication

yes

Source-replica replication

Database mirroring

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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.

yes

GPU vRAM or System RAM

yes

User concepts

Access control

Access rights for users and roles on table level

Access rights for users and organizations can be defined via Rockset console

fine grained access rights according to SQL-standard

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