DBMS > Apache Impala vs. EventStoreDB vs. GreptimeDB vs. SAP HANA

System Properties Comparison Apache Impala vs. EventStoreDB vs. GreptimeDB vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Industrial-strength, open-source database solution built from the ground up for event sourcing.

An open source Time Series DBMS built for increased scalability, high performance and efficiency

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

Primary database model

Secondary database models

Document store

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	1.19
Rank	#173	Overall
	#1	Event Stores

Score	0.12
Rank	#351	Overall
	#34	Time Series DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

impala.apache.org

www.eventstore.com

greptime.com

www.sap.com/products/hana.html

Technical documentation

impala.apache.org/impala-docs.html

developers.eventstore.com

docs.greptime.com

help.sap.com/hana

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Event Store Limited

Greptime Inc.

SAP

Initial release

2013

2012

2022

2010

Current release

4.1.0, June 2022

21.2, February 2021

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

commercial

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

C++

Rust

Server operating systems

Linux

Linux
Windows

Android
Docker
FreeBSD
Linux
macOS
Windows

Appliance or cloud-service

Data scheme

yes

schema-free, schema definition possible

yes

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

gRPC
HTTP API
JDBC

JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

C++
Erlang
Go
Java
JavaScript

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Python

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Simple rights management via user accounts

yes

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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Key customers

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Market metrics

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Licensing and pricing models

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