DBMS > SAP HANA vs. Spark SQL vs. TypeDB vs. XTDB

System Properties Comparison SAP HANA vs. Spark SQL vs. TypeDB vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

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

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

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

Document store

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	0.70
Rank	#230	Overall
	#20	Graph DBMS
	#106	Relational DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

www.sap.com/products/hana.html

spark.apache.org/sql

typedb.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

help.sap.com/hana

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

typedb.com/docs

www.xtdb.com/docs

Developer

SAP

Apache Software Foundation

Vaticle

Juxt Ltd.

Initial release

2010

2014

2016

2019

Current release

2.0 SPS07 (April 4, 2023), April 2023

3.5.0 ( 2.13), September 2023

2.26.3, January 2024

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GPL Version 3, commercial licenses available

Open Source

MIT License

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

Scala

Java

Clojure

Server operating systems

Appliance or cloud-service

Linux
OS X
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

yes

SQL-like DML and DDL statements

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
ODBC

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

HTTP REST
JDBC

Supported programming languages

Java
Python
R
Scala

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

Clojure
Java

Server-side scripts

Stored procedures

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

yes, utilizing Spark Core

Sharding

by using Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication

by using Cassandra

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

by using Apache Kafka and Apache Zookeeper

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

substituted by the relationship feature

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, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

yes

User concepts

Access control

yes

at REST API level; other APIs in progress

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Licensing and pricing models

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