DBMS > GreptimeDB vs. HarperDB vs. Lovefield vs. ObjectBox vs. Sphinx

System Properties Comparison GreptimeDB vs. HarperDB vs. Lovefield vs. ObjectBox vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

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

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.

Embeddable relational database for web apps written in pure JavaScript

Extremely fast embedded database for small devices, IoT and Mobile

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Secondary database models

Time Series DBMS

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

Score	0.12
Rank	#351	Overall
	#34	Time Series DBMS

Score	0.60
Rank	#244	Overall
	#38	Document stores

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

greptime.com

www.harperdb.io

google.github.io/lovefield

objectbox.io

sphinxsearch.com

Technical documentation

docs.greptime.com

docs.harperdb.io/docs

github.com/google/lovefield/blob/master/docs/spec_index.md

docs.objectbox.io

sphinxsearch.com/docs

Developer

Greptime Inc.

HarperDB

Google

ObjectBox Limited

Sphinx Technologies Inc.

Initial release

2022

2017

2014

2017

2001

Current release

3.1, August 2021

2.1.12, February 2017

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free community edition available

Open Source

Apache 2.0

Open Source

Apache License 2.0

Open Source

GPL version 2, commercial licence available

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

Rust

Node.js

JavaScript

C and C++

C++

Server operating systems

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux
OS X

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Android
iOS
Linux
macOS
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

schema-free, schema definition possible

dynamic schema

yes

Typing

predefined data types such as float or date

yes

JSON data types

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

full-text index on all search fields

SQL

Support of SQL

yes

SQL-like data manipulation statements

SQL-like query language

via JavaScript builder pattern

SQL-like query language (SphinxQL)

APIs and other access methods

gRPC
HTTP API
JDBC

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

Proprietary native API

Proprietary protocol

Supported programming languages

C++
Erlang
Go
Java
JavaScript

.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

JavaScript

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

Python

Custom Functions

since release 3.1

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

yes

the nodes on which a table resides can be defined

none

online/offline synchronization between client and server

none

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

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

The original contents of fields are not stored in the Sphinx index.

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

Simple rights management via user accounts

Access rights for users and roles

yes

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

News

The on-device Vector Database for Android and Java
29 May 2024

Vector search: making sense of search queries
29 May 2024

Python on-device Vector and Object Database for Local AI
28 May 2024

Evolution of search: traditional vs vector search
23 May 2024

On-device Vector Database for Dart/Flutter
21 May 2024

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

DB-Engines blog posts

The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

show all

Recent citations in the news

Serent Capital invests in software firm HarperDB
12 June 2024, PE Hub

HarperDB Attracts Significant Growth Investment from Serent Capital
12 June 2024, Business Wire

HarperDB Receives Growth Investment from Serent Capital
12 June 2024, FinSMEs

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

Jaxon Repp on HarperDB Distributed Database Platform
23 March 2022, InfoQ.com

provided by Google News

ObjectBox Raises $2M in Funding
4 December 2018, FinSMEs

The Megashift Towards Decentralized Edge Computing
27 August 2021, hackernoon.com

provided by Google News

Switching From Sphinx to MkDocs Documentation — What Did I Gain and Lose
2 February 2024, Towards Data Science

5 Powerful Alternatives to Elasticsearch
25 April 2024, Insider Monkey

Manticore is a Faster Alternative to Elasticsearch in C++
25 July 2022, hackernoon.com

Royal Mail stamp prices could rise, warns Czech Sphinx
3 June 2024, Proactive Investors UK

Perplexity AI: From Its Use To Operation, Everything You Need To Know About Google's Newest Challenger
11 January 2024, Free Press Journal

provided by Google News

Share this page