DBMS > Apache Druid vs. Lovefield vs. PostgreSQL vs. SAP Adaptive Server vs. TempoIQ

System Properties Comparison Apache Druid vs. Lovefield vs. PostgreSQL vs. SAP Adaptive Server vs. TempoIQ

Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

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

Embeddable relational database for web apps written in pure JavaScript

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

Spatial DBMS

with Boeing's Spatial Query Server

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	#293	Overall
	#133	Relational DBMS

Score	645.54
Rank	#4	Overall
	#4	Relational DBMS

Score	36.31
Rank	#25	Overall
	#17	Relational DBMS

Website

druid.apache.org

google.github.io/lovefield

www.postgresql.org

www.sap.com/products/technology-platform/sybase-ase.html

tempoiq.com (offline)

Technical documentation

druid.apache.org/docs/latest/design

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

www.postgresql.org/docs

help.sap.com/docs/SAP_ASE

Developer

Apache Software Foundation and contributors

Google

PostgreSQL Global Development Group

www.postgresql.org/developer

SAP, Sybase

TempoIQ

Initial release

2012

2014

1989

1989: Postgres, 1996: PostgreSQL

1987

2012

Current release

29.0.1, April 2024

2.1.12, February 2017

16.3, May 2024

16.0

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache 2.0

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

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Implementation language

Java

JavaScript

C and C++

Server operating systems

Linux
OS X
Unix

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

tested with Chrome, Firefox, IE, Safari

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

AIX
HP-UX
Linux
Solaris
Unix
Windows

Data scheme

yes

schema-less columns are supported

yes

schema-free

Typing

predefined data types such as float or date

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

SQL-like query language

via JavaScript builder pattern

yes

standard with numerous extensions

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

HTTP API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

JavaScript

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C
C++
Cobol
Java
Java
Perl
PHP
Python

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Java and Transact-SQL

Triggers

Using read-only observers

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

partitioning by range, list and (since PostgreSQL 11) by hash

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

none

Source-replica replication

other methods possible by using 3rd party extensions

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

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

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

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

fine grained access rights according to SQL-standard

simple authentication-based access control

More information provided by the system vendor

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