DBMS > Apache Druid vs. Graph Engine vs. SingleStore vs. TempoIQ

System Properties Comparison Apache Druid vs. Graph Engine vs. SingleStore vs. TempoIQ

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Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

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

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Primary database model

Relational DBMS
Time Series DBMS

Graph DBMS
Key-value store

Relational DBMS

Time Series DBMS

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	3.29
Rank	#95	Overall
	#49	Relational DBMS
	#7	Time Series DBMS

Score	0.62
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	5.91
Rank	#61	Overall
	#34	Relational DBMS

Website

druid.apache.org

www.graphengine.io

www.singlestore.com

tempoiq.com (offline)

Technical documentation

druid.apache.org/docs/latest/design

www.graphengine.io/docs/manual

docs.singlestore.com

Developer

Apache Software Foundation and contributors

Microsoft

SingleStore Inc.

TempoIQ

Initial release

2012

2010

2013

2012

Current release

29.0.1, April 2024

8.5, January 2024

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

MIT License

commercial

free developer edition available

commercial

Cloud-based only

Only available as a cloud service

yes

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

Java

.NET and C

C++, Go

Server operating systems

Linux
OS X
Unix

.NET

Linux

64 bit version required

Data scheme

yes

schema-less columns are supported

yes

schema-free

Typing

predefined data types such as float or date

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

SQL

Support of SQL

SQL for querying

yes

but no triggers and foreign keys

APIs and other access methods

JDBC
RESTful HTTP/JSON API

RESTful HTTP API

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

HTTP API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C#
C++
F#
Visual Basic

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

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

horizontal partitioning

Sharding

hash partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

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

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

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

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

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

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Fine grained access control via users, groups and roles

simple authentication-based access control

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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

Licensing and pricing models

F ree Tier and Enterprise Edition
» more

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