Featured Products: Milvus AllegroGraph Datastax Astra RaimaDB Neo4j

DBMS > EsgynDB vs. Google Cloud Bigtable vs. Graph Engine vs. HarperDB vs. SQL.JS

System Properties Comparison EsgynDB vs. Google Cloud Bigtable vs. Graph Engine vs. HarperDB vs. SQL.JS

Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

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.

Port of SQLite to JavaScript

Primary database model

Relational DBMS

Key-value store
Wide column store

Graph DBMS
Key-value store

Relational DBMS

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

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	0.53
Rank	#252	Overall
	#116	Relational DBMS

Website

cloud.google.com/bigtable

www.graphengine.io

www.harperdb.io

Technical documentation

cloud.google.com/bigtable/docs

www.graphengine.io/docs/manual

docs.harperdb.io/docs

sql.js.org/documentation/index.html

Developer

Esgyn

Google

Microsoft

HarperDB

Alon Zakai

enhancements implemented by others

Initial release

2015

2015

2010

2017

2012

Current release

3.1, August 2021

License

Commercial or Open Source

commercial

commercial

Open Source

MIT License

commercial

free community edition available

Open Source

Cloud-based only

Only available as a cloud service

no

yes

no

no

no

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++, Java

.NET and C

Node.js

JavaScript

Server operating systems

Linux

hosted

.NET

Linux
OS X

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

Data scheme

yes

schema-free

yes

dynamic schema

yes

Typing

predefined data types such as float or date

yes

no

yes

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.

no

no

no

no

no

Secondary indexes

yes

no

yes

SQL

Support of SQL

yes

no

no

SQL-like data manipulation statements

yes

SQL-92 is not fully supported

APIs and other access methods

ADO.NET
JDBC
ODBC

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

RESTful HTTP API

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

JavaScript API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

C#
C++
Go
Java
JavaScript (Node.js)
Python

C#
C++
F#
Visual Basic

.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

Server-side scripts

Stored procedures

Java Stored Procedures

no

yes

Custom Functions

since release 3.1

no

Triggers

no

no

no

no

no

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding

horizontal partitioning

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Internal replication in Colossus, and regional replication between two clusters in different zones

yes

the nodes on which a table resides can be defined

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes

no

no

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

none

Foreign keys

Referential integrity

yes

no

no

no

yes

Transaction concepts

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

ACID

Atomic single-row operations

no

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes

yes

yes

Durability

Support for making data persistent

yes

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes, using LMDB

no

except by serializing a db to a file

In-memory capabilities

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

no

no

yes

yes

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Access rights for users and roles

no

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

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

Recent citations in the news

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs
31 January 2022, InfoQ.com

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

Google scales up Cloud Bigtable NoSQL database
27 January 2022, TechTarget

Google Cloud makes it cheaper to run smaller workloads on Bigtable
7 April 2020, TechCrunch

provided by Google News

Trinity
2 June 2023, Microsoft

Open source Microsoft Graph Engine takes on Neo4j
13 February 2017, InfoWorld

IBM releases Graph, a service that can outperform SQL databases
27 July 2016, GeekWire

Aerospike Is Now a Graph Database, Too
21 June 2023, Datanami

The graph analytics landscape 2019 - DataScienceCentral.com
27 February 2019, Data Science Central

provided by Google 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 | ZDNET
7 February 2018, ZDNet

HarperDB 4.0 Delivers Enterprise-Grade Global Application Development to Every Developer
17 January 2023, Markets Insider

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

provided by Google News

9 Best JavaScript and TypeScript ORMs for 2024 — SitePoint
22 March 2023, SitePoint

Execute millions of SQL statements in milliseconds in the browser with WebAssembly and Web Workers.
14 January 2017, hackernoon.com

SQLite On The Web: Absurd-sql
24 August 2021, Hackaday

In Praise Of SQLite
28 July 2022, iProgrammer

Running PostgreSQL Inside Your Browser
8 September 2022, iProgrammer

provided by Google News

Share this page

Featured Products

Present your product here