DBMS > Apache Pinot vs. GreptimeDB vs. Microsoft Azure Table Storage vs. Sadas Engine vs. UniData,UniVerse

System Properties Comparison Apache Pinot vs. GreptimeDB vs. Microsoft Azure Table Storage vs. Sadas Engine vs. UniData,UniVerse

Editorial information provided by DB-Engines

Name

Description

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

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

A Wide Column Store for rapid development using massive semi-structured datasets

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

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

Score	0.38
Rank	#275	Overall
	#126	Relational DBMS

Score	0.12
Rank	#351	Overall
	#34	Time Series DBMS

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	2.85
Rank	#98	Overall
	#1	Multivalue DBMS

Website

pinot.apache.org

greptime.com

azure.microsoft.com/en-us/services/storage/tables

www.sadasengine.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

docs.pinot.apache.org

docs.greptime.com

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Apache Software Foundation and contributors

Greptime Inc.

Microsoft

SADAS s.r.l.

Rocket Software

Initial release

2015

2022

2012

2006

1985

Current release

1.0.0, September 2023

8.0

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

commercial

free trial version available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Rust

C++

Server operating systems

All OS with a Java JDK11 or higher

Android
Docker
FreeBSD
Linux
macOS
Windows

hosted

AIX
Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free, schema definition possible

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

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 query language

yes

APIs and other access methods

JDBC

gRPC
HTTP API
JDBC

RESTful HTTP API

JDBC
ODBC
Proprietary protocol

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

Go
Java
Python

C++
Erlang
Go
Java
JavaScript

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
C
C#
C++
Groovy
Java
PHP
Python

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

Python

yes

Triggers

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Implicit feature of the cloud service

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

none

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

optimistic locking

ACID

configurable

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

managed by 'Learn by Usage'

User concepts

Access control

Simple rights management via user accounts

Access rights based on private key authentication or shared access signatures

Access rights for users, groups and roles according to SQL-standard

Access rights according to SQL-standard and operating system based

More information provided by the system vendor

Specific characteristics

GreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more

Competitive advantages

- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more

Typical application scenarios

For IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more

Key customers

Greptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more

Market metrics

GreptimeDB has garnered global recognition by topping GitHub trends following its...
» more

Licensing and pricing models

GreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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