DBMS > NSDb vs. Transwarp Hippo vs. Yaacomo

System Properties Comparison NSDb vs. Transwarp Hippo vs. Yaacomo

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Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

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

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Time Series DBMS

Vector DBMS

Relational DBMS

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

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	0.05
Rank	#386	Overall
	#16	Vector DBMS

Website

nsdb.io

www.transwarp.cn/en/subproduct/hippo

yaacomo.com

Technical documentation

nsdb.io/Architecture

Developer

Q2WEB GmbH

Initial release

2017

2023

2009

Current release

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

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Implementation language

Java, Scala

C++

Server operating systems

Linux
macOS

Android
Linux
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes: int, bigint, decimal, string

Vector, Numeric and String

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

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

gRPC
HTTP REST
WebSocket

RESTful HTTP API

JDBC
ODBC

Supported programming languages

Java
Scala

C++
Java
Python

Server-side scripts

Stored procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Using Apache Lucene

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

Role based access control and fine grained access rights

fine grained access rights according to SQL-standard

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