DBMS > Amazon Redshift vs. Ignite vs. Microsoft Azure Data Explorer vs. SingleStore vs. Titan

System Properties Comparison Amazon Redshift vs. Ignite vs. Microsoft Azure Data Explorer vs. SingleStore vs. Titan

Editorial information provided by DB-Engines

Name

Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.

Description

Large scale data warehouse service for use with business intelligence tools

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Fully managed big data interactive analytics platform

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

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

column oriented

Relational DBMS

Graph DBMS

Secondary database models

Document store

If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store

this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine

support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	3.11
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	3.80
Rank	#81	Overall
	#43	Relational DBMS

Score	5.38
Rank	#62	Overall
	#35	Relational DBMS

Website

aws.amazon.com/redshift

ignite.apache.org

azure.microsoft.com/services/data-explorer

www.singlestore.com

github.com/thinkaurelius/titan

Technical documentation

docs.aws.amazon.com/redshift

apacheignite.readme.io/docs

docs.microsoft.com/en-us/azure/data-explorer

docs.singlestore.com

github.com/thinkaurelius/titan/wiki

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Microsoft

SingleStore Inc.

Aurelius, owned by DataStax

Initial release

2012

2015

2019

2013

2012

Current release

Apache Ignite 2.6

cloud service with continuous releases

8.5, January 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

free developer edition available

Open Source

Apache license, version 2.0

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

C++, Java, .Net

C++, Go

Java

Server operating systems

hosted

Linux
OS X
Solaris
Windows

hosted

Linux

64 bit version required

Linux
OS X
Unix
Windows

Data scheme

yes

Fixed schema with schema-less datatypes (dynamic)

yes

Typing

predefined data types such as float or date

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-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.

yes

Secondary indexes

restricted

yes

all fields are automatically indexed

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

ANSI-99 for query and DML statements, subset of DDL

Kusto Query Language (KQL), SQL subset

yes

but no triggers and foreign keys

APIs and other access methods

JDBC
ODBC

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

All languages supporting JDBC/ODBC

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

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

Clojure
Java
Python

Server-side scripts

Stored procedures

user defined functions

in Python

yes (compute grid and cache interceptors can be used instead)

Yes, possible languages: KQL, Python, R

yes

Triggers

yes (cache interceptors and events)

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

hash partitioning

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes (replicated cache)

yes

Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Source-replica replication

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

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Spark connector (open source): github.com/Azure/azure-kusto-spark

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

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Relationships in graph

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

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

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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 rights according to SQL-standard

Security Hooks for custom implementations

Azure Active Directory Authentication

Fine grained access control via users, groups and roles

User authentification and security via Rexster Graph Server

More information provided by the system vendor

Specific characteristics

SingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
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Competitive advantages

SingleStore’s competitive advantages include: Easy and Simplified Architecture with...
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Typical application scenarios

Driving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
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Key customers

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

Customers in various industries worldwide including US and International Industry...
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Licensing and pricing models

F ree Tier and Enterprise Edition
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