DBMS > Kinetica vs. LeanXcale vs. RRDtool vs. SAP HANA vs. Stardog

System Properties Comparison Kinetica vs. LeanXcale vs. RRDtool vs. SAP HANA vs. Stardog

Editorial information provided by DB-Engines

Name

Description

Fully vectorized database across both GPUs and CPUs

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

In-memory, column based data store. Available as appliance or cloud service

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Time Series DBMS

Relational DBMS

Graph DBMS
RDF store

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

www.kinetica.com

www.leanxcale.com

oss.oetiker.ch/rrdtool

www.sap.com/products/hana.html

www.stardog.com

Technical documentation

docs.kinetica.com

oss.oetiker.ch/rrdtool/doc

help.sap.com/hana

docs.stardog.com

Developer

Kinetica

LeanXcale

Tobias Oetiker

SAP

Stardog-Union

Initial release

2012

2015

1999

2010

Current release

7.1, August 2021

1.8.0, 2022

2.0 SPS07 (April 4, 2023), April 2023

7.3.0, May 2020

License

Commercial or Open Source

commercial

Open Source

GPL V2 and FLOSS

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++

Implementations in Java (e.g. RRD4J) and C# available

Java

Server operating systems

Linux

HP-UX
Linux

Appliance or cloud-service

Linux
macOS
Windows

Data scheme

yes

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

yes

Numeric data only

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.

Exporting into and restoring from XML files possible

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

SQL-like DML and DDL statements

yes

through Apache Derby

yes

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

in-process shared library
Pipes

JDBC
ODBC

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

C++
Java
JavaScript (Node.js)
Python

C
Java
Scala

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

SQLScript, R

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

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

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

yes

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

none

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

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.

yes

GPU vRAM or System RAM

yes

User concepts

Access control

Access rights for users and roles on table level

yes

Access rights for users and roles

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