DBMS > Apache Drill vs. SAP HANA vs. TimescaleDB vs. Vertica

System Properties Comparison Apache Drill vs. SAP HANA vs. TimescaleDB vs. Vertica

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

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

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Document store
Relational DBMS

Relational DBMS

Time Series DBMS

Relational DBMS

Column oriented

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Relational DBMS

Spatial DBMS
Time Series DBMS

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

Score	2.02
Rank	#124	Overall
	#22	Document stores
	#59	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	4.46
Rank	#71	Overall
	#5	Time Series DBMS

Score	10.06
Rank	#42	Overall
	#26	Relational DBMS

Website

drill.apache.org

www.sap.com/products/hana.html

www.timescale.com

www.vertica.com

Technical documentation

drill.apache.org/docs

help.sap.com/hana

docs.timescale.com

vertica.com/documentation

Developer

Apache Software Foundation

SAP

Timescale

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2012

2010

2017

2005

Current release

1.20.3, January 2023

2.0 SPS07 (April 4, 2023), April 2023

2.15.0, May 2024

12.0.3, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Apache 2.0

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

also available as a cloud based service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Server operating systems

Linux
OS X
Windows

Appliance or cloud-service

Linux
OS X
Windows

Linux

Data scheme

schema-free

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

full PostgreSQL SQL syntax

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

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

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

C++

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

Server-side scripts

Stored procedures

user defined functions

SQLScript, R

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

yes, across time and space (hash partitioning) attributes

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication with hot standby and reads on replicas

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

Depending on the underlying data source

yes

In-memory capabilities

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

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

yes

fine grained access rights according to SQL-standard

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

Specific characteristics

Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more

Competitive advantages

Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more

Typical application scenarios

Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more

Key customers

Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more

Licensing and pricing models

Cost-based models and subscription-based models are both available. One license is...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.