DBMS > Axibase vs. Lovefield vs. Netezza vs. Spark SQL vs. STSdb

System Properties Comparison Axibase vs. Lovefield vs. Netezza vs. Spark SQL vs. STSdb

Editorial information provided by DB-Engines

Name

Description

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

Embeddable relational database for web apps written in pure JavaScript

Data warehouse and analytics appliance part of IBM PureSystems

Spark SQL is a component on top of 'Spark Core' for structured data processing

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Time Series DBMS

Relational DBMS

Key-value store

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

Score	0.35
Rank	#282	Overall
	#25	Time Series DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

axibase.com/docs/atsd/finance

google.github.io/lovefield

www.ibm.com/products/netezza

spark.apache.org/sql

github.com/STSSoft/STSdb4

Technical documentation

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

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Axibase Corporation

Google

IBM

Apache Software Foundation

STS Soft SC

Initial release

2013

2014

2000

2014

2011

Current release

15585

2.1.12, February 2017

3.5.0 ( 2.13), September 2023

4.0.8, September 2015

License

Commercial or Open Source

commercial

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

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0

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

JavaScript

Scala

Server operating systems

Linux

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

tested with Chrome, Firefox, IE, Safari

Linux

included in appliance

Linux
OS X
Windows

Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

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

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

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

yes

SQL-like DML and DDL statements

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

JDBC
ODBC
OLE DB

JDBC
ODBC

.NET Client API

Supported programming languages

Go
Java
PHP
Python
R
Ruby

JavaScript

C
C++
Fortran
Java
Lua
Perl
Python
R

Java
Python
R
Scala

C#
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

Users with fine-grained authorization concept

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