DBMS > Apache Pinot vs. SpaceTime vs. Transwarp Hippo

System Properties Comparison Apache Pinot vs. SpaceTime vs. Transwarp Hippo

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

Relational DBMS

Spatial DBMS

Vector DBMS

Secondary database models

Relational DBMS

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

Score	0.38
Rank	#275	Overall
	#126	Relational DBMS

Score	0.03
Rank	#392	Overall
	#8	Spatial DBMS

Score	0.05
Rank	#386	Overall
	#16	Vector DBMS

Website

pinot.apache.org

www.mireo.com/spacetime

www.transwarp.cn/en/subproduct/hippo

Technical documentation

docs.pinot.apache.org

Developer

Apache Software Foundation and contributors

Mireo

Initial release

2015

2020

2023

Current release

1.0.0, September 2023

1.0, May 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++

Server operating systems

All OS with a Java JDK11 or higher

Linux

Linux
macOS

Data scheme

yes

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

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

SQL

Support of SQL

SQL-like query language

A subset of ANSI SQL is implemented

APIs and other access methods

JDBC

RESTful HTTP API

Supported programming languages

Go
Java
Python

C#
C++
Python

C++
Java
Python

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Fixed-grid hypercubes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Real-time block device replication (DRBD)

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

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

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

yes

Role based access control and fine grained access rights

More information provided by the system vendor

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

StarTree broadly enhances Apache Pinot-based analytics platform
8 May 2024, SiliconANGLE News

StarTree Finds Apache Pinot the Right Vintage for IT Observability
8 May 2024, Datanami

Real-Time Analytics for Mobile App Crashes using Apache Pinot
2 November 2023, Uber

Apache Pinot - SD Times Open Source Project of the Week
31 May 2024, SDTimes.com

Open source Apache Pinot advances as StarTree boosts real-time analytics and observability
8 May 2024, VentureBeat

provided by Google News

Share this page