DBMS > Axibase vs. Kdb vs. Lovefield vs. SAP HANA vs. Sphinx

System Properties Comparison Axibase vs. Kdb vs. Lovefield vs. SAP HANA vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

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

High performance Time Series DBMS

Embeddable relational database for web apps written in pure JavaScript

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

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Time Series DBMS

Time Series DBMS
Vector DBMS

Relational DBMS

Search engine

Secondary database models

Relational 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	0.29
Rank	#292	Overall
	#25	Time Series DBMS

Score	7.55
Rank	#53	Overall
	#3	Time Series DBMS
	#1	Vector DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

axibase.com/docs/atsd/finance

kx.com

google.github.io/lovefield

www.sap.com/products/hana.html

sphinxsearch.com

Technical documentation

code.kx.com

github.com/google/lovefield/blob/master/docs/spec_index.md

help.sap.com/hana

sphinxsearch.com/docs

Developer

Axibase Corporation

Kx Systems, a division of First Derivatives plc

Google

SAP

Sphinx Technologies Inc.

Initial release

2013

2000

kdb was released 2000, kdb+ in 2003

2014

2010

2001

Current release

15585

3.6, May 2018

2.1.12, February 2017

2.0 SPS07 (April 4, 2023), April 2023

3.5.1, February 2023

License

Commercial or Open Source

commercial

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

commercial

free 32-bit version

Open Source

Apache 2.0

commercial

Open Source

GPL version 2, commercial licence available

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

Java

JavaScript

C++

Server operating systems

Linux

Linux
OS X
Solaris
Windows

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Appliance or cloud-service

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

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

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.

yes

Secondary indexes

yes

table attribute 'grouped'

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like query language

SQL-like query language (q)

SQL-like query language

via JavaScript builder pattern

yes

SQL-like query language (SphinxQL)

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

JDBC
ODBC

Proprietary protocol

Supported programming languages

Go
Java
PHP
Python
R
Ruby

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

JavaScript

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

user defined functions

SQLScript, R

Triggers

yes

with views

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

yes

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

similar paradigm used for internal processing

Consistency concepts

Methods to ensure consistency in a distributed system

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

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

The original contents of fields are not stored in the Sphinx index.

In-memory capabilities

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

yes

using MemoryDB

yes

User concepts

Access control

rights management via user accounts

yes

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...
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Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
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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...
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Licensing and pricing models

upon request
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