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

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

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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

An AI-native realtime vector database engine that integrates scalable machine learning models.

Primary database model

Document store
Relational DBMS

Relational DBMS

Time Series DBMS

Vector DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Relational 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	1.52
Rank	#153	Overall
	#5	Vector DBMS

Website

drill.apache.org

www.sap.com/products/hana.html

www.timescale.com

github.com/weaviate/weaviate
weaviate.io

Technical documentation

drill.apache.org/docs

help.sap.com/hana

docs.timescale.com

weaviate.io/developers/weaviate

Developer

Apache Software Foundation

SAP

Timescale

Weaviate B.V.

Initial release

2012

2010

2017

2019

Current release

1.20.3, January 2023

2.0 SPS07 (April 4, 2023), April 2023

2.15.0, May 2024

1.19, May 2023

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Apache 2.0

Open Source

commercial license available with Weaviate Enterprise

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

Server operating systems

Linux
OS X
Windows

Appliance or cloud-service

Linux
OS X
Windows

Data scheme

schema-free

yes

yes, maps to GraphQL interface

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

string, int, float, geo point, date, cross reference, fuzzy references

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

all data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

full PostgreSQL SQL syntax

GraphQL is used as query language

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

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

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

C++

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

JavaScript / TypeScript
Python

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

yes, across time and space (hash partitioning) attributes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication with hot standby and reads on replicas

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual 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

API Keys
OpenID Connect Discovery

More information provided by the system vendor

Specific characteristics

Weaviate is an open source vector database that is robust, scalable, cloud-native,...
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Competitive advantages

Flexible deployment - Free, open source or fully-managed cloud vector database service...
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Typical application scenarios

As a database supporting the development of generative AI and semantic search applications...
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Key customers

All companies that have data.
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Market metrics

As of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
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Licensing and pricing models

Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
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