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DBMS > Apache Drill vs. Hazelcast vs. Microsoft Azure Data Explorer vs. Sqrrl vs. Tarantool

System Properties Comparison Apache Drill vs. Hazelcast vs. Microsoft Azure Data Explorer vs. Sqrrl vs. Tarantool

Editorial information provided by DB-Engines
NameApache Drill  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSqrrl  Xexclude from comparisonTarantool  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionSchema-free SQL Query Engine for Hadoop, NoSQL and Cloud StorageA widely adopted in-memory data gridFully managed big data interactive analytics platformAdaptable, secure NoSQL built on Apache AccumuloIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelDocument store
Relational DBMS
Key-value storeRelational DBMS infocolumn orientedDocument store
Graph DBMS
Key-value store
Wide column store
Document store
Key-value store
Relational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Document store infoIf 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 infothis 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 infosupport 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 infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
Spatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.95
Rank#127  Overall
#23  Document stores
#60  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Websitedrill.apache.orghazelcast.comazure.microsoft.com/­services/­data-explorersqrrl.comwww.tarantool.io
Technical documentationdrill.apache.org/­docshazelcast.org/­imdg/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerwww.tarantool.io/­en/­doc
DeveloperApache Software FoundationHazelcastMicrosoftAmazon infooriginally Sqrrl Data, Inc.VK
Initial release20122008201920122008
Current release1.20.3, January 20235.3.6, November 2023cloud service with continuous releases2.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2; commercial licenses availablecommercialcommercialOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC and C++
Server operating systemsLinux
OS X
Windows
All OS with a Java VMhostedLinuxBSD
Linux
macOS
Data schemeschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)schema-freeFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesstring, double, decimal, uuid, integer, blob, boolean, datetime
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.noyes infothe object must implement a serialization strategyyesno
Secondary indexesnoyesall fields are automatically indexedyesyes
SQL infoSupport of SQLSQL SELECT statement is SQL:2003 compliantSQL-like query languageKusto Query Language (KQL), SQL subsetnoFull-featured ANSI SQL support
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Open binary protocol
Supported programming languagesC++.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresuser defined functionsyes infoEvent Listeners, Executor ServicesYes, possible languages: KQL, Python, RnoLua, C and SQL stored procedures
Triggersnoyes infoEventsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceSharding infomaking use of HadoopSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated Mapyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor infomaking use of HadoopAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyes
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Immediate Consistency
Immediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.Casual 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 integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoone or two-phase-commit; repeatable reads; read commitednoAtomic updates per row, document, or graph entityACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, cooperative multitasking
Durability infoSupport for making data persistentDepending on the underlying data sourceyesyesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Depending on the underlying data sourceyesnoyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlDepending on the underlying data sourceRole-based access controlAzure Active Directory AuthenticationCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources
Apache DrillHazelcastMicrosoft Azure Data ExplorerSqrrlTarantool
DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
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