DBMS > HarperDB vs. IBM Db2 Event Store vs. STSdb vs. Transwarp Hippo

System Properties Comparison HarperDB vs. IBM Db2 Event Store vs. STSdb vs. Transwarp Hippo

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

Distributed Event Store optimized for Internet of Things use cases

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

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

Primary database model

Document store

Event Store
Time Series DBMS

Key-value store

Vector DBMS

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

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Score	0.00
Rank	#383	Overall
	#13	Vector DBMS

Website

www.harperdb.io

www.ibm.com/products/db2-event-store

github.com/STSSoft/STSdb4

www.transwarp.cn/en/subproduct/hippo

Technical documentation

docs.harperdb.io/docs

www.ibm.com/docs/en/db2-event-store

Developer

HarperDB

IBM

STS Soft SC

Initial release

2017

2011

2023

Current release

3.1, August 2021

2.0

4.0.8, September 2015

1.0, May 2023

License

Commercial or Open Source

commercial

free community edition available

commercial

free developer edition available

Open Source

GPLv2, commercial license available

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

Node.js

C and C++

C++

Server operating systems

Linux
OS X

Linux

Linux, macOS, Windows for the developer addition

Windows

Linux
macOS

Data scheme

dynamic schema

yes

Typing

predefined data types such as float or date

yes

JSON data types

yes

primitive types and user defined types (classes)

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

yes

SQL

Support of SQL

SQL-like data manipulation statements

yes

through the embedded Spark runtime

APIs and other access methods

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

.NET Client API

RESTful HTTP API

Supported programming languages

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

C#
Java

C++
Java
Python

Server-side scripts

Stored procedures

Custom Functions

since release 3.1

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

A table resides as a whole on one (or more) nodes in a cluster

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

the nodes on which a table resides can be defined

Active-active shard replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of specific operations

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes, using LMDB

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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 and roles

fine grained access rights according to SQL-standard

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

Startups of the Year 2023: Meet HarperDB - A Database and Application Development Platform
22 June 2023, hackernoon.com

Unlocking immersive golfing experiences with AWS Wavelength | Amazon Web Services
29 November 2022, AWS Blog

HarperDB: An underdog SQL / NoSQL database
7 February 2018, ZDNet

HarperDB is More Than Just a Database: Here's Why
21 August 2021, hackernoon.com

Stephen Goldberg Named 2023 Bill Daniels Ethical Leader of the Year | CU Denver Business School News
9 January 2023, business-news.ucdenver.edu

provided by Google News

Advancements in streaming data storage, real-time analysis and machine learning
25 July 2019, ibm.com

IBM Builds New Ultra-Fast Platform for Hoovering Up and Analyzing Data from Anywhere
31 May 2018, Data Center Knowledge

How IBM Is Turning Db2 into an 'AI Database'
3 June 2019, Datanami

Best cloud databases of 2022
4 October 2022, ITPro

provided by Google News

Share this page