DBMS > BigObject vs. EJDB vs. Hypertable vs. Newts vs. SingleStore

System Properties Comparison BigObject vs. EJDB vs. Hypertable vs. Newts vs. SingleStore

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

Analytic DBMS for real-time computations and queries

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

An open source BigTable implementation based on distributed file systems such as Hadoop

Time Series DBMS based on Cassandra

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Secondary database models

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	5.60
Rank	#62	Overall
	#35	Relational DBMS

Website

bigobject.io

github.com/Softmotions/ejdb

opennms.github.io/newts

www.singlestore.com

Technical documentation

docs.bigobject.io

github.com/Softmotions/ejdb/blob/master/README.md

github.com/OpenNMS/newts/wiki

docs.singlestore.com

Developer

BigObject, Inc.

Softmotions

Hypertable Inc.

OpenNMS Group

SingleStore Inc.

Initial release

2015

2012

2009

2014

2013

Current release

0.9.8.11, March 2016

8.5, January 2024

License

Commercial or Open Source

commercial

free community edition available

Open Source

GPLv2

Open Source

GNU version 3. Commercial license available

Open Source

Apache 2.0

commercial

free developer edition 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.

SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities

Implementation language

C++

Java

C++, Go

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

server-less

Linux
OS X
Windows

an inofficial Windows port is available

Linux
OS X
Windows

Linux

64 bit version required

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

but no triggers and foreign keys

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

in-process shared library

C++ API
Thrift

HTTP REST
Java API

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

C++
Java
Perl
PHP
Python
Ruby

Java

Bash
C
C#
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Lua

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

Sharding

hash partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor on file system level

selectable replication factor

based on Cassandra

Source-replica replication

stores two copies of each physical data partition on two separate nodes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

can define user-defined aggregate functions for map-reduce-style calculations

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Read/Write Locking

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

In-memory capabilities

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

yes

User concepts

Access control

Fine grained access control via users, groups and roles

More information provided by the system vendor

Specific characteristics

SingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
» more

Competitive advantages

SingleStore’s competitive advantages include: Easy and Simplified Architecture with...
» more

Typical application scenarios

Driving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
» more

Key customers

IEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,...
» more

Market metrics

Customers in various industries worldwide including US and International Industry...
» more

Licensing and pricing models

F ree Tier and Enterprise Edition
» more

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

Turbocharge Your Application Development Using WebAssembly With SingleStoreDB
17 October 2022, Akmal Chaudhri, SingleStore (sponsor)

Cloud-Based Analytics With SingleStoreDB
9 June 2022, Akmal Chaudhri, SingleStore (sponsor)

SingleStore: The Increasing Momentum of Multi-Model Database Systems
14 February 2022, Akmal Chaudhri, SingleStore (sponsor)

show all

Recent citations in the news

SQL and TimescaleDB. This article takes a closer look into… | by Alibaba Cloud
31 July 2019, DataDrivenInvestor

TimescaleDB goes distributed; implements ‘Chunking’ over ‘Sharding’ for scaling-out
22 August 2019, Packt Hub

Decorate your Windows XP with Hyperdesk
30 July 2008, CNET

The Collective: Customize Your Computer & Your Phone With Star Trek
18 March 2009, TrekMovie

NoSQL Market: A well-defined technological growth map with an impact-analysis
19 June 2020, Inter Press Service

provided by Google News

SingleStore CEO sees little future for purpose-built vector databases
24 January 2024, VentureBeat

SingleStore Announces Real-time Data Platform to Further Accelerate AI, Analytics and Application Development
24 January 2024, Business Wire

Building a Modern Database: Nikita Shamgunov on Postgres and Beyond
17 April 2024, Madrona Venture Group

SingleStore adds indexed vector search to Pro Max release for faster AI work – Blocks and Files
29 January 2024, Blocks & Files

Announcing watsonx.ai and SingleStore for generative AI applications
15 November 2023, IBM

provided by Google News

Share this page