DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Ignite vs. Microsoft Azure Cosmos DB vs. Sadas Engine vs. Tarantool vs. TDengine

System Properties Comparison Ignite vs. Microsoft Azure Cosmos DB vs. Sadas Engine vs. Tarantool vs. TDengine

Editorial information provided by DB-Engines
NameIgnite  Xexclude from comparisonMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparisonSadas Engine  Xexclude from comparisonTarantool  Xexclude from comparisonTDengine  Xexclude from comparison
DescriptionApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Globally distributed, horizontally scalable, multi-model database serviceSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsTime Series DBMS and big data platform
Primary database modelKey-value store
Relational DBMS
Document store
Graph DBMS
Key-value store
Wide column store
Relational DBMSDocument store
Key-value store
Relational DBMS
Time Series DBMS
Secondary database modelsSpatial DBMSSpatial DBMS infowith Tarantool/GIS extensionRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score29.04
Rank#27  Overall
#4  Document stores
#2  Graph DBMS
#3  Key-value stores
#3  Wide column stores
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Score2.60
Rank#107  Overall
#8  Time Series DBMS
Websiteignite.apache.orgazure.microsoft.com/­services/­cosmos-dbwww.sadasengine.comwww.tarantool.iogithub.com/­taosdata/­TDengine
tdengine.com
Technical documentationapacheignite.readme.io/­docslearn.microsoft.com/­azure/­cosmos-dbwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationwww.tarantool.io/­en/­docdocs.tdengine.com
DeveloperApache Software FoundationMicrosoftSADAS s.r.l.VKTDEngine, previously Taos Data
Initial release20152014200620082019
Current releaseApache Ignite 2.68.02.10.0, May 20223.0, August 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercial infofree trial version availableOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool EnterpriseOpen Source infoAGPL V3, also commercial editions available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, Java, .NetC++C and C++C
Server operating systemsLinux
OS X
Solaris
Windows
hostedAIX
Linux
Windows
BSD
Linux
macOS
Linux
Windows
Data schemeyesschema-freeyesFlexible data schema: relational definition for tables with ability to store json-like documents in columnsyes
Typing infopredefined data types such as float or dateyesyes infoJSON typesyesstring, double, decimal, uuid, integer, blob, boolean, datetimeyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.yesnonono
Secondary indexesyesyes infoAll properties auto-indexed by defaultyesyesno
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLSQL-like query languageyesFull-featured ANSI SQL supportStandard SQL with extensions for time-series applications
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
JDBC
ODBC
Proprietary protocol
Open binary protocolJDBC
RESTful HTTP API
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
.Net
C
C#
C++
Groovy
Java
PHP
Python
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)JavaScriptnoLua, C and SQL stored proceduresno
Triggersyes (cache interceptors and events)JavaScriptnoyes, before/after data modification events, on replication events, client session eventsyes, via alarm monitoring
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicehorizontal partitioningSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)yes infoImplicit feature of the cloud servicenoneAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)with Hadoop integration infoIntegration with Hadoop/HDInsight on Azure*no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyBounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency infoConsistency level configurable on request level
Session Consistency
Immediate ConsistencyCasual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Foreign keys infoReferential integritynonoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDMulti-item ACID transactions with snapshot isolation within a partitionACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, cooperative multitaskingyes
Durability infoSupport for making data persistentyesyesyesyes, write ahead loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infomanaged by 'Learn by Usage'yes, full featured in-memory storage engine with persistence
User concepts infoAccess controlSecurity Hooks for custom implementationsAccess rights can be defined down to the item levelAccess rights for users, groups and roles according to SQL-standardAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
yes
More information provided by the system vendor
IgniteMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBSadas EngineTarantoolTDengine
Specific characteristicsTDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
» more
Competitive advantagesHigh Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more
Typical application scenariosTDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more
Market metricsTDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more
Licensing and pricing modelsTDengine OSS is an open source, cloud native time series database. It includes built-in...
» more
News

Can Typical Time-Series Databases Replace Data Historians?
8 May 2024

TDengine 3.3.0.0 Release Notes
7 May 2024

How to Unlock Value from Industrial Data with AI and ML Technology
6 May 2024

Compare InfluxDB vs. TDengine
19 April 2024

Why We Need the Next Generation Data Historian
15 April 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
3rd partiesCData: Connect to Big Data & NoSQL through standard Drivers.
» more

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
IgniteMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBSadas EngineTarantoolTDengine
DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021,  Vladimir Perepelytsya, Tarantool (sponsor) 

show all

Recent citations in the news

GridGain Announces Call for Speakers for Virtual Apache Ignite Summit 2024
8 February 2024, PR Newswire

Apache Ignite: An Overview
6 September 2023, Open Source For You

GridGain Releases Conference Schedule for Virtual Apache Ignite Summit 2023
1 June 2023, Datanami

What is Apache Ignite? How is Apache Ignite Used?
18 July 2022, The Stack

Real-time in-memory OLTP and Analytics with Apache Ignite on AWS | Amazon Web Services
14 May 2016, AWS Blog

provided by Google News

Start your AI journey with Microsoft Azure Cosmos DB—compete for $10K | Azure Blog
8 May 2024, Microsoft

Public preview: Change partition key of a container in Azure Cosmos DB (NoSQL API) | Azure updates
27 March 2024, Microsoft

Evaluating Performance: CosmosDB vs. Azure SQL
16 January 2024, Хабр

Azure Synapse Link for Cosmos DB: New Analytics Capabilities
10 November 2023, InfoQ.com

How to Migrate Azure Cosmos DB Databases | by Arwin Lashawn
25 August 2023, DataDrivenInvestor

provided by Google News

In-Memory Showdown: Redis vs. Tarantool
4 April 2023, Хабр

TaranHouse: New Big Data Warehouse Announced by Tarantool
4 April 2018, Newswire

Deploying Tarantool Cartridge applications with zero effort (Part 1)
16 December 2019, Хабр

Deploying Tarantool Cartridge applications with zero effort (Part 2)
13 April 2020, Хабр

Тarantool Cartridge: Sharding Lua Backend in Three Lines
9 October 2019, Хабр

provided by Google News

TDengine debuts cloud-based time-series data processing platform for IoT deployments
20 September 2022, SiliconANGLE News

New TDengine Benchmark Results Show Up to 37.0x Higher Query Performance Than InfluxDB and TimescaleDB
28 February 2023, GlobeNewswire

Comparing Different Time-Series Databases
10 February 2022, hackernoon.com

provided by Google News



Share this page

Featured Products

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

AllegroGraph logo

Graph Database Leader for AI Knowledge Graph Applications - The Most Secure Graph Database Available.
Free Download

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Present your product here